IDEAS home Printed from https://ideas.repec.org/a/gam/jagris/v4y2014i4p288-307d43317.html
   My bibliography  Save this article

Small Ruminant Production System Efficiency under Abu-Dhabi, United Arab Emirates Arid Land Conditions

Author

Listed:
  • Eihab Fathelrahman

    (Department of Agribusiness and Consumer Sciences, College of Food and Agriculture, United Arab Emirates University, P.O. Box 15551, Al Ain, United Arab Emirates)

  • Sherin Sherif

    (Economics and Agribusiness Department, Faculty of Agriculture, Alexandria University, El-Shatby, P.O. Box 21545, Alexandria, Egypt)

  • Dana L. K. Hoag

    (Department of Agriculture and Natural Resource Economics, College of Agriculture, Colorado State University, B330 Clark Building, Fort Collins, CO 80523, USA)

Abstract

Sheep and goat production systems in the United Arab Emirates (UAE) operate under scarce natural resource constraints. A cross-sectional survey that covered 661 mixed farms, including major sheep and goat production, was conducted in the three regions of Abu Dhabi Emirate (Al-Ain, Western Region and Abu Dhabi city) during 2012. A Cobb-Douglas, double-logarithmic stochastic frontier production function and maximum likelihood estimation were applied to estimate important economic derivatives and the associated risk of small ruminant production in this arid area. The highest impact of an input on the output level was found to be labor for raising sheep and alfalfa grass for raising goats. Both labor and alfalfa variables were found to be overutilized for sheep and goat production, respectively. Overall, the results indicate that average technical efficiency is 0.62 for raising sheep and only 0.34 for raising goats in the study area. Technical efficiency analysis included measuring the frequency of farms at each level of estimated technical efficiency in the range between zero and one. Zero for the technical efficiency coefficient indicates a lack of technical efficiency in resource use. The results of this study indicated that only 1% of the sheep farms show a technical efficiency coefficient of 0.25 or less; the same can be said for 41% of goat producers. However, these technical efficiencies were found to be more than 0.75 for 12% and 5% of the sheep and goat farms, respectively. Overall, goat farming in the UAE was found to be less efficient than sheep production. The results also indicated that flock size and type of breed were the most influential factors relative to other factors, and both show a positive relationship with technical efficiency. Other than flock size, factors, such as owners’ years of experience and management practices, were found to be more influential on goat farming system efficiency relative to sheep farming.

Suggested Citation

  • Eihab Fathelrahman & Sherin Sherif & Dana L. K. Hoag, 2014. "Small Ruminant Production System Efficiency under Abu-Dhabi, United Arab Emirates Arid Land Conditions," Agriculture, MDPI, vol. 4(4), pages 1-20, December.
    • Handle: RePEc:gam:jagris:v:4:y:2014:i:4:p:288-307:d:43317
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2077-0472/4/4/288/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2077-0472/4/4/288/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Fuss, Melvyn & McFadden, Daniel, 1978. "Production Economics: A Dual Approach to Theory and Applications (II): Applications of the Theory of Production," History of Economic Thought Books, McMaster University Archive for the History of Economic Thought, volume 2, number fuss1978a.
    2. Fuss, Melvyn & McFadden, Daniel & Mundlak, Yair, 1978. "A Survey of Functional Forms in the Economic Analysis of Production," Histoy of Economic Thought Chapters, in: Fuss, Melvyn & McFadden, Daniel (ed.),Production Economics: A Dual Approach to Theory and Applications, volume 1, chapter 4, McMaster University Archive for the History of Economic Thought.
    3. Jondrow, James & Knox Lovell, C. A. & Materov, Ivan S. & Schmidt, Peter, 1982. "On the estimation of technical inefficiency in the stochastic frontier production function model," Journal of Econometrics, Elsevier, vol. 19(2-3), pages 233-238, August.
    4. Hall, Harry H., 1998. "Choosing an Empirical Production Function: Theory, Nonnested Hypotheses, Costs of Specifications," Agricultural Economics Research Reports 31977, University of Kentucky, Department of Agricultural Economics.
    5. Chambers,Robert G., 1988. "Applied Production Analysis," Cambridge Books, Cambridge University Press, number 9780521314275, October.
    6. Villano, Renato A. & Fleming, Euan M. & Fleming, Pauline, 2008. "Measuring Regional Productivity Differences in the Australian Wool Industry: A Metafrontier Approach," 2008 Conference (52nd), February 5-8, 2008, Canberra, Australia 6036, Australian Agricultural and Resource Economics Society.
    7. David Hadley, 2006. "Patterns in Technical Efficiency and Technical Change at the Farm‐level in England and Wales, 1982–2002," Journal of Agricultural Economics, Wiley Blackwell, vol. 57(1), pages 81-100, March.
    8. Roberto Furesi & Fabio Madau & Pietro Pulina, 2013. "Technical efficiency in the sheep dairy industry: an application on the Sardinian (Italy) sector," Demography, Springer;Population Association of America (PAA), vol. 1(1), pages 1-11, December.
    9. Kumar, Shalander, 2007. "Commercial Goat Farming in India: An Emerging Agri-Business Opportunity," Agricultural Economics Research Review, Agricultural Economics Research Association (India), vol. 20(Conferenc).
    10. Fuss, Melvyn & McFadden, Daniel (ed.), 1978. "Production Economics: A Dual Approach to Theory and Applications," Elsevier Monographs, Elsevier, edition 1, number 9780444850133.
    11. Griffin, Ronald C. & Montgomery, John M. & Rister, M. Edward, 1987. "Selecting Functional Form In Production Function Analysis," Western Journal of Agricultural Economics, Western Agricultural Economics Association, vol. 12(2), pages 1-12, December.
    12. Fuss, Melvyn & McFadden, Daniel, 1978. "Production Economics: A Dual Approach to Theory and Applications (I): The Theory of Production," History of Economic Thought Books, McMaster University Archive for the History of Economic Thought, volume 1, number fuss1978.
    13. Suresh, A. & Gupta, D.C. & Mann, J.S., 2008. "Returns and Economic Efficiency of Sheep Farming in Semi-arid Regions: A Study in Rajasthan," Agricultural Economics Research Review, Agricultural Economics Research Association (India), vol. 21(2).
    14. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
    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. V. Vandenberghe, 2018. "The Contribution of Educated Workers to Firms’ Efficiency Gains: The Key Role of Proximity to the ‘Local’ Frontier," De Economist, Springer, vol. 166(3), pages 259-283, September.
    2. Jean Pierre Huiban & Camille Mastromarco & Antonio Musolesi & Michel Simioni, 2016. "The impact of pollution abatement investments on production technology: new insights from frontier analysis," Working Papers hal-01512154, HAL.
    3. Taining Wang & Jinjing Tian & Feng Yao, 2021. "Does high debt ratio influence Chinese firms’ performance? A semiparametric stochastic frontier approach with zero inefficiency," Empirical Economics, Springer, vol. 61(2), pages 587-636, August.
    4. repec:kap:iaecre:v:14:y:2008:i:1:p:76-89 is not listed on IDEAS
    5. Perekhozhuk, Oleksandr, 2007. "Marktstruktur und Preisbildung auf dem ukrainischen Markt für Rohmilch," Studies on the Agricultural and Food Sector in Transition Economies, Leibniz Institute of Agricultural Development in Transition Economies (IAMO), volume 41, number 92322.
    6. Kumbhakar, Subal C. & Wang, Hung-Jen, 2006. "Estimation of technical and allocative inefficiency: A primal system approach," Journal of Econometrics, Elsevier, vol. 134(2), pages 419-440, October.
    7. Tiziana Laureti, 2008. "Modelling Exogenous Variables in Human Capital Formation through a Heteroscedastic Stochastic Frontier," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 14(1), pages 76-89, February.
    8. Hess, Sebastian & Surry, Yves R., 2011. "The CDET Profit Function: Could it generate a Parsimonious Agricultural Sector Model?," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 114539, European Association of Agricultural Economists.
    9. Sauer, J., 2007. "Monotonicity and Curvature – A Bootstrapping Approach," Proceedings “Schriften der Gesellschaft für Wirtschafts- und Sozialwissenschaften des Landbaues e.V.”, German Association of Agricultural Economists (GEWISOLA), vol. 42, March.
    10. Dairo Estrada & Poldy Osorio, 2004. "Effects of Financial Capital on Colombian Banking Efficiency," Revista ESPE - Ensayos sobre Política Económica, Banco de la Republica de Colombia, vol. 22(47), pages 162-201, December.
    11. Andrea Mantovi, 2016. "Smooth preferences, symmetries and expansion vector fields," Journal of Economics, Springer, vol. 119(2), pages 147-169, October.
    12. T. A. Bhavani & Suresh Tendulkar, 2001. "Determinants of firm-level export performance: a case study of Indian textile garments and apparel industry," The Journal of International Trade & Economic Development, Taylor & Francis Journals, vol. 10(1), pages 65-92.
    13. Tocco,Barbara & Bailey, Alastair & Davidova, Sophia, 2013. "The Theoretical Framework and Methodology to Estimate the Farm Labour and Other Factor-Derived Demand and Output Supply Systems," Factor Markets Working Papers 156, Centre for European Policy Studies.
    14. repec:hal:spmain:info:hdl:2441/2041 is not listed on IDEAS
    15. Gabriele Dono & Luca Giraldo & Simone Severini, 2012. "The Cost of Irrigation Water Delivery: An Attempt to Reconcile the Concepts of Cost and Efficiency," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(7), pages 1865-1877, May.
    16. Florian Pelgrin & Arnaud Sylvain & Eric Heyer, 2004. "Capital operating time and working time in the production function : an evaluation on a panel firms over the period 1989-2001," SciencePo Working papers Main hal-00972838, HAL.
    17. T.A Bhavani & Suresh D. Tendulkar, 2000. "Determinants of Firm-level Export Performance: A Case Study of Indian Textile Garments and Apparel Industry," Working papers 81, Centre for Development Economics, Delhi School of Economics.
    18. Levent Kutlu & Shasha Liu & Robin C. Sickles, 2022. "Cost, Revenue, and Profit Function Estimates," Springer Books, in: Subhash C. Ray & Robert G. Chambers & Subal C. Kumbhakar (ed.), Handbook of Production Economics, chapter 16, pages 641-679, Springer.
    19. Konstantinos Giannakas & K. Tran & Vangelis Tzouvelekas, 1999. "On the Choice of Functional Form in Stochastic Frontiers Models: A Box-Cox Approach," Working Papers 9915, University of Crete, Department of Economics.
    20. Martin, Juan Carlos & Voltes-Dorta, Augusto, 2007. "Marginal Cost Estimations In Airports. Multiproductive Cost Functions And Stochastic Frontiers: An International Airports Case Study," 48th Annual Transportation Research Forum, Boston, Massachusetts, March 15-17, 2007 207931, Transportation Research Forum.
    21. Sauer, Johannes, 2006. "Monotonicity And Curvature - A Bootstrapping Approach," 46th Annual Conference, Giessen, Germany, October 4-6, 2006 14948, German Association of Agricultural Economists (GEWISOLA).
    22. T.A. Bhavani & Suresh D. Tendulkar, 2010. "Determinants of Firm-level Export Performance: A Case Study of Indian Textile Garments and Apparel Industry," Working Papers id:2964, eSocialSciences.

    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:jagris:v:4:y:2014:i:4:p:288-307:d:43317. 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.