IDEAS home Printed from https://ideas.repec.org/a/gam/jagris/v12y2022i10p1742-d949651.html
   My bibliography  Save this article

Technical Efficiency Analysis of Layer and Broiler Poultry Farmers in Pakistan

Author

Listed:
  • Nisar Ahmed Khan

    (School of Economics and Management, Beijing University of Technology, Beijing 100081, China)

  • Majid Ali

    (Department of Economics and Agi-Economics, PMAS-Arid Agriculture University, Rawalpindi 46000, Pakistan)

  • Nihal Ahmad

    (School of Economics and Management, Northwest Agricultural & Forestry University, Xi’an 712100, China)

  • Muhammad Ali Abid

    (Department of Artificial Intelligence, University of Agriculture Dera Ismail Khan, Dera Ismail Khan 29120, Pakistan)

  • Sigrid Kusch-Brandt

    (Faculty of Mathematics, Natural Sciences and Management, University of Applied Sciences Ulm, 89075 Ulm, Germany
    Water and Environmental Engineering Group, University of Southampton, Southampton SO16 7QF, UK)

Abstract

Achieving high production with limited resources is a major challenge faced by poultry farmers in countries with developing economies, such as Pakistan. Optimization of the technical efficiency (TE) of poultry business operations is a promising strategy. A representative sample of 210 poultry farms in the province of Punjab in Pakistan was analyzed for TE. The studied sample comprised 105 layer chicken farms (battery cage system, egg production) and 105 broiler chicken farms (environmental control shed system, meat production). A Cobb–Douglas stochastic frontier production analysis approach with the inefficiency effect model was used to simultaneously estimate TE levels and identify factors that influence efficiency. The results indicated that flock size, labor, feed, and water consumption are positively related to egg production, whereas vaccination was found to be insignificant. For broiler businesses, flock size, feed, and water consumption were positively related to the output, whereas labor and vaccination were found to be insignificant. The results of the TE inefficiency effect model revealed that farmer age, education, experience, access to credit, and access to extension services all had a significant and positive influence on the technical efficiency of both layer and broiler farmers. The estimated mean TE level of layer and broiler poultry farmers was 89% and 92%, respectively, evaluated against the benchmark of the identified frontier of efficient production with prevailing systems. The study concludes that it is possible to increase egg production by 11% and meat production by 8% by making more efficient use of the available resources and technology. To improve poultry farmers’ efficiency, policy interventions should focus more on the pronounced effects of variables such as education, farmer experience, credit access, and extension services.

Suggested Citation

  • Nisar Ahmed Khan & Majid Ali & Nihal Ahmad & Muhammad Ali Abid & Sigrid Kusch-Brandt, 2022. "Technical Efficiency Analysis of Layer and Broiler Poultry Farmers in Pakistan," Agriculture, MDPI, vol. 12(10), pages 1-21, October.
  • Handle: RePEc:gam:jagris:v:12:y:2022:i:10:p:1742-:d:949651
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2077-0472/12/10/1742/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2077-0472/12/10/1742/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Coelli, Tim J., 1995. "Recent Developments In Frontier Modelling And Efficiency Measurement," Australian Journal of Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 39(3), pages 1-27, December.
    2. Lindikaya W. Myeki & Nkhanedzeni B. Nengovhela & Livhuwani Mudau & Elvis Nakana & Simphiwe Ngqangweni, 2022. "Estimation of Technical, Allocative, and Economic Efficiencies for Smallholder Broiler Producers in South Africa," Agriculture, MDPI, vol. 12(10), pages 1-14, October.
    3. Yenibehit, N. & Murshed, M. & Islam, M. J., 2019. "Assessment of Technical Efficiency of Layer Production in Mampong Municipality: Stochastic Frontier Approach," Current Research in Agricultural Sciences, Conscientia Beam, vol. 6(1), pages 20-28.
    4. Mulugeta Y. Birhanu & Tesfahun Alemayehu & Jasmine E. Bruno & Fasil Getachew Kebede & Emmanuel Babafunso Sonaiya & Ezekiel H. Goromela & Oladeji Bamidele & Tadelle Dessie, 2021. "Technical Efficiency of Traditional Village Chicken Production in Africa: Entry Points for Sustainable Transformation and Improved Livelihood," Sustainability, MDPI, vol. 13(15), pages 1-21, July.
    5. Prabhat Khanal & Rajan Dhakal & Tanka Khanal & Deepak Pandey & Naba Raj Devkota & Mette Olaf Nielsen, 2022. "Sustainable Livestock Production in Nepal: A Focus on Animal Nutrition Strategies," Agriculture, MDPI, vol. 12(5), pages 1-20, May.
    6. Meeusen, Wim & van den Broeck, Julien, 1977. "Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 435-444, June.
    7. Tiange Liu & Sherryl Broverman & Eve S. Puffer & Daniel A. Zaltz & Andrew L. Thorne-Lyman & Sara E. Benjamin-Neelon, 2022. "Dietary Diversity and Dietary Patterns in School-Aged Children in Western Kenya: A Latent Class Analysis," IJERPH, MDPI, vol. 19(15), pages 1-12, July.
    8. Saliu, L.A. & Abdulrazaq, S.A. & Eleke, P.N., 2016. "Production Efficiency of Poultry Egg (Layer) Production in Chikun and Igabi Local Government Areas of Kaduna State, Nigeria," Nigerian Journal of Agricultural Economics, Nigerian Journal of Agricultural Economics, vol. 6(1), October.
    9. Stevenson, Rodney E., 1980. "Likelihood functions for generalized stochastic frontier estimation," Journal of Econometrics, Elsevier, vol. 13(1), pages 57-66, May.
    10. Muhammad Kamran Hanif & Yahui Fan & Lina Wang & Hong Jiang & Zhaofang Li & Mei Ma & Le Ma & Mao Ma, 2022. "Dietary Habits of Patients with Coronary Artery Disease: A Case-Control Study from Pakistan," IJERPH, MDPI, vol. 19(14), pages 1-9, July.
    11. Yanqi Han & Hui Lyu & Shixiong Cheng & Yuhang He, 2022. "Influencing Mechanism and Difference of Poultry Farmers’ Willingness and Behavior in Breeding Scale—Evidence from Jianghan Plain, China," IJERPH, MDPI, vol. 19(3), pages 1-15, January.
    12. Yenibehit N & Murshed M & Islam M. J, 2019. "Assessment of Technical Efficiency of Layer Production in Mampong Municipality: Stochastic Frontier Approach," Current Research in Agricultural Sciences, Conscientia Beam, vol. 6(1), pages 20-28.
    13. 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. Wasantha Athukorala & Clevo Wilson, 2012. "Groundwater overuse and farm-level technical inefficiency: evidence from Sri Lanka," School of Economics and Finance Discussion Papers and Working Papers Series 279, School of Economics and Finance, Queensland University of Technology.
    2. Yongil Jeon & Ishak Haji Omar & K. Kuperan & Dale Squires & Indah Susilowati, 2006. "Developing country fisheries and technical efficiency: the Java Sea purse seine fishery," Applied Economics, Taylor & Francis Journals, vol. 38(13), pages 1541-1552.
    3. Sakouvogui Kekoura & Shaik Saleem & Doetkott Curt & Magel Rhonda, 2021. "Sensitivity analysis of stochastic frontier analysis models," Monte Carlo Methods and Applications, De Gruyter, vol. 27(1), pages 71-90, March.
    4. Quoc Ngu Vu, 2002. "Technical Efficiency of Vietnamese Industrial SOEs and Non-SOEs," International and Development Economics Working Papers idec02-6, International and Development Economics.
    5. 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.
    6. Reinhard, Stijn & Knox Lovell, C. A. & Thijssen, Geert J., 2000. "Environmental efficiency with multiple environmentally detrimental variables; estimated with SFA and DEA," European Journal of Operational Research, Elsevier, vol. 121(2), pages 287-303, March.
    7. Mai, Nhat Chi, 2015. "Efficiency of the banking system in Vietnam under financial liberalization," OSF Preprints qsf6d, Center for Open Science.
    8. John K M & Wayo Seini, 2013. "Technical Efficiency Analysis of Maize Farmers in the Eastern Region of Ghana," Journal of Social and Development Sciences, AMH International, vol. 4(2), pages 84-99.
    9. Jerzy Marzec & Andrzej Pisulewski & Artur Prędki, 2019. "Efektywność techniczna i produktywność polskich gospodarstw rolnych specjalizujących się w uprawach polowych," Gospodarka Narodowa. The Polish Journal of Economics, Warsaw School of Economics, issue 2, pages 95-125.
    10. Ali M. Oumer & Amin Mugera & Michael Burton & Atakelty Hailu, 2022. "Technical efficiency and firm heterogeneity in stochastic frontier models: application to smallholder maize farms in Ethiopia," Journal of Productivity Analysis, Springer, vol. 57(2), pages 213-241, April.
    11. Suzanne O’Neill & Alan Matthews, 2001. "Technical Change and Efficiency in Irish Agriculture," The Economic and Social Review, Economic and Social Studies, vol. 32(3), pages 263-284.
    12. Nguyen Hung Anh & Wolfgang Bokelmann & Do Thi Nga & Nguyen Van Minh, 2019. "Toward Sustainability or Efficiency: The Case of Smallholder Coffee Farmers in Vietnam," Economies, MDPI, vol. 7(3), pages 1-25, July.
    13. Rossi, Martín, 2000. "Análisis de eficiencia aplicado a la regulación ¿Es importante la Distribución Elegida para el Término de Ineficiencia?," UADE Textos de Discusión 22_2000, Instituto de Economía, Universidad Argentina de la Empresa.
    14. Noel Uri, 2003. "The Effect of Incentive Regulation in Telecommunications in the United States," Quality & Quantity: International Journal of Methodology, Springer, vol. 37(2), pages 169-191, May.
    15. Rosen Azad Chowdhury & Dilshad Jahan & Tapas Mishra & Mamata Parhi, 2023. "A Quality Dimension? A Re-appraisal of Financial Development and Economic Growth Nexus in a Quality-Quantity Setting," Working Papers 2023-02, Swansea University, School of Management.
    16. Roy, Manish & Mazumder, Ritwik, 2016. "Technical Efficiency of Fish Catch in Traditional Fishing: A Study in Southern Assam," Journal of Regional Development and Planning, Rajarshi Majumder, vol. 5(1), pages 55-68.
    17. Vaneet Bhatia & Sankarshan Basu & Subrata Kumar Mitra & Pradyumna Dash, 2018. "A review of bank efficiency and productivity," OPSEARCH, Springer;Operational Research Society of India, vol. 55(3), pages 557-600, November.
    18. William Griffiths & Xiaohui Zhang & Xueyan Zhao, 2010. "A Stochastic Frontier Model for Discrete Ordinal Outcomes: A Health Production Function," Department of Economics - Working Papers Series 1092, The University of Melbourne.
    19. Gil, Guilherme Dôco Roberti & Costa, Marcelo Azevedo & Lopes, Ana Lúcia Miranda & Mayrink, Vinícius Diniz, 2017. "Spatial statistical methods applied to the 2015 Brazilian energy distribution benchmarking model: Accounting for unobserved determinants of inefficiencies," Energy Economics, Elsevier, vol. 64(C), pages 373-383.
    20. I. Fraser & W. Horrace, 2003. "Technical Efficiency of Australian Wool Production: Point and Confidence Interval Estimates," Journal of Productivity Analysis, Springer, vol. 20(2), pages 169-190, September.

    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:12:y:2022:i:10:p:1742-:d:949651. 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.