IDEAS home Printed from https://ideas.repec.org/p/ags/aesc11/108947.html
   My bibliography  Save this paper

Technical efficiency and technology gaps in beef cattle production systems in Kenya: A stochastic metafrontier analysis

Author

Listed:
  • Otieno, David Jakinda
  • Hubbard, Lionel J.
  • Ruto, Eric

Abstract

In this study the stochastic metafrontier method is used to investigate technical efficiency and technology gaps across three main beef cattle production systems in Kenya. Results show that there is significant inefficiency in nomadic and agro-pastoral systems. Further, in contrast with ranches, these two systems were found to have lower technology gap ratios. The average pooled technical efficiency was estimated to be 0.69, which suggests that there is considerable scope to improve beef production in Kenya

Suggested Citation

  • Otieno, David Jakinda & Hubbard, Lionel J. & Ruto, Eric, 2011. "Technical efficiency and technology gaps in beef cattle production systems in Kenya: A stochastic metafrontier analysis," 85th Annual Conference, April 18-20, 2011, Warwick University, Coventry, UK 108947, Agricultural Economics Society.
  • Handle: RePEc:ags:aesc11:108947
    DOI: 10.22004/ag.econ.108947
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/108947/files/61Otieno_hubbard_ruto.pdf
    Download Restriction: no

    File URL: https://libkey.io/10.22004/ag.econ.108947?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
    ---><---

    References listed on IDEAS

    as
    1. Chih-Hai Yang & Ku-Hsieh Chen, 2009. "Are small firms less efficient?," Small Business Economics, Springer, vol. 32(4), pages 375-395, April.
    2. Coelli, Tim J. & Battese, George E., 1996. "Identification Of Factors Which Influence The Technical Inefficiency Of Indian Farmers," Australian Journal of Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 40(2), pages 1-26, August.
    3. George E. Battese & Greg S. Corra, 1977. "Estimation Of A Production Frontier Model: With Application To The Pastoral Zone Of Eastern Australia," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 21(3), pages 169-179, December.
    4. Huang, Yi-Ju & Chen, Ku-Hsieh & Yang, Chih-Hai, 2010. "Cost efficiency and optimal scale of electricity distribution firms in Taiwan: An application of metafrontier analysis," Energy Economics, Elsevier, vol. 32(1), pages 15-23, January.
    5. George Battese & D. Rao & Christopher O'Donnell, 2004. "A Metafrontier Production Function for Estimation of Technical Efficiencies and Technology Gaps for Firms Operating Under Different Technologies," Journal of Productivity Analysis, Springer, vol. 21(1), pages 91-103, January.
    6. Carol Newman & Alan Matthews, 2006. "The productivity performance of Irish dairy farms 1984–2000: a multiple output distance function approach," Journal of Productivity Analysis, Springer, vol. 26(2), pages 191-205, October.
    7. MacDonald, James M. & Perry, Janet E. & Ahearn, Mary Clare & Banker, David E. & Chambers, William & Dimitri, Carolyn & Key, Nigel D. & Nelson, Kenneth E. & Southard, Leland W., 2004. "Contracts, Markets, and Prices: Organizing the Production and Use of Agricultural Commodities," Agricultural Economic Reports 34013, United States Department of Agriculture, Economic Research Service.
    8. Willam Greene, 2005. "Fixed and Random Effects in Stochastic Frontier Models," Journal of Productivity Analysis, Springer, vol. 23(1), pages 7-32, January.
    9. Muyanga, Milu & Jayne, Thom S., 2006. "Agricultural Extension in Kenya: Practice and Policy Lessons," Working Papers 202617, Egerton University, Tegemeo Institute of Agricultural Policy and Development.
    10. Efthymios G. Tsionas, 2002. "Stochastic frontier models with random coefficients," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(2), pages 127-147.
    11. George E. Battese & D. S. Prasada Rao, 2002. "Technology Gap, Efficiency, and a Stochastic Metafrontier Function," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 1(2), pages 87-93, August.
    12. P. Irungu & J. M. Omiti & L. G. Mugunieri, 2006. "Determinants of farmers' preference for alternative animal health service providers in Kenya: a proportional hazard application," Agricultural Economics, International Association of Agricultural Economists, vol. 35(1), pages 11-17, July.
    13. Andrew Barnes, 2008. "Technical Efficiency Estimates of Scottish Agriculture: A Note," Journal of Agricultural Economics, Wiley Blackwell, vol. 59(2), pages 370-376, June.
    14. Awudu Abdulai & Hendrik Tietje, 2007. "Estimating technical efficiency under unobserved heterogeneity with stochastic frontier models: application to northern German dairy farms," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 34(3), pages 393-416, September.
    15. Luis Orea & Subal C. Kumbhakar, 2004. "Efficiency measurement using a latent class stochastic frontier model," Empirical Economics, Springer, vol. 29(1), pages 169-183, January.
    16. Rakipova, Anna N. & Gillespie, Jeffrey M. & Franke, Donald E., 2003. "Determinants of Technical Efficiency in Louisiana Beef Cattle Production," Journal of the ASFMRA, American Society of Farm Managers and Rural Appraisers, vol. 2003, pages 1-9.
    17. Kodde, David A & Palm, Franz C, 1986. "Wald Criteria for Jointly Testing Equality and Inequality Restriction s," Econometrica, Econometric Society, vol. 54(5), pages 1243-1248, September.
    18. Gamba, Paul, 2006. "Beef and Dairy Cattle Improvement Services: A Policy Perspective," Working Papers 202620, Egerton University, Tegemeo Institute of Agricultural Policy and Development.
    19. Antonio Alvarez & Julio del Corral, 2010. "Identifying different technologies using a latent class model: extensive versus intensive dairy farms," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 37(2), pages 231-250, June.
    20. Battese, George E. & Corra, Greg S., 1977. "Estimation Of A Production Frontier Model: With Application To The Pastoral Zone Of Eastern Australia," Australian Journal of Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 21(3), pages 1-11, December.
    21. 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.
    22. Hossein Mehrabi Boshrabadi & Renato Villano & Euan Fleming, 2008. "Technical efficiency and environmental‐technological gaps in wheat production in Kerman province of Iran," Agricultural Economics, International Association of Agricultural Economists, vol. 38(1), pages 67-76, January.
    23. Hayami, Yujiro & Ruttan, Vernon W, 1970. "Agricultural Productivity Differences Among Countries," American Economic Review, American Economic Association, vol. 60(5), pages 895-911, December.
    24. Chen, Zhuo & Song, Shunfeng, 2008. "Efficiency and technology gap in China's agriculture: A regional meta-frontier analysis," China Economic Review, Elsevier, vol. 19(2), pages 287-296, June.
    25. Johannes Sauer & Klaus Frohberg & Henrich Hockmann, 2006. "Stochastic efficiency measurement: The curse of theoretical consistency," Journal of Applied Economics, Universidad del CEMA, vol. 9, pages 139-166, May.
    26. Yanyan Liu & Robert Myers, 2009. "Model selection in stochastic frontier analysis with an application to maize production in Kenya," Journal of Productivity Analysis, Springer, vol. 31(1), pages 33-46, February.
    27. Christopher O’Donnell & D. Rao & George Battese, 2008. "Metafrontier frameworks for the study of firm-level efficiencies and technology ratios," Empirical Economics, Springer, vol. 34(2), pages 231-255, March.
    28. 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.
    29. 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.
    30. 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.
    31. Chavas, Jean-Paul & Aliber, Michael, 1993. "An Analysis Of Economic Efficiency In Agriculture: A Nonparametric Approach," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 18(1), pages 1-16, July.
    32. Xiaobing Wang & Supawat Rungsuriyawiboon, 2010. "Agricultural efficiency, technical change and productivity in China," Post-Communist Economies, Taylor & Francis Journals, vol. 22(2), pages 207-227.
    33. Featherstone, Allen M. & Langemeier, Michael R. & Ismet, Mohammad, 1997. "A Nonparametric Analysis of Efficiency for a Sample of Kansas Beef Cow Farms," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 29(1), pages 175-184, July.
    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. Yongjie Xue & Jinling Yan & Yongfu Cui & Huifeng Zhao & Ya’nan Zhang & Changhai Ma & Haijing Zheng, 2022. "The Technical Efficiency of Beef Calf Production Systems: Evidence from a Survey in Hebei, China," Agriculture, MDPI, vol. 12(10), pages 1-22, October.
    2. Missiame, Arnold & Irungu, Patrick & Nyikal, Rose Adhiambo, 2021. "Gender-differentiated stochastic meta-frontier analysis of production technology heterogeneity among smallholder cassava farmers in Ghana," African Journal of Agricultural and Resource Economics, African Association of Agricultural Economists, vol. 16(2), June.

    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. Nwigwe, Cecilia & Okoruwa, Victor & Obi-Egbedi, Oghenerueme, 2015. "Efficiency differentials and technological gaps in beef cattle production systems in Nigeria," 2015 Conference, August 9-14, 2015, Milan, Italy 229377, International Association of Agricultural Economists.
    2. Otieno, David Jakinda & Hubbard, Lionel J. & Ruto, Eric, 2012. "Determinants of technical efficiency in beef cattle production in Kenya," 2012 Conference, August 18-24, 2012, Foz do Iguacu, Brazil 125853, International Association of Agricultural Economists.
    3. Bahta, Sirak & Baker, Derek & Malope, Patrick & Katijuongua, Hikuepi, 2015. "A metafronteir analysis of determinants of technical efficiency in beef farm types: an application to Botswana," 2015 Conference, August 9-14, 2015, Milan, Italy 211194, International Association of Agricultural Economists.
    4. Xiangfei Xin & Yi Zhang & Jimin Wang & John Alexander Nuetah, 2016. "Effects of Farm Size on Technical Efficiency in China's Broiler Sector: A Stochastic Meta-Frontier Approach," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 64(3), pages 493-516, September.
    5. Gatti, Nicolas & Lema, Daniel & Brescia, Victor, 2015. "A Meta-Frontier Approach to Measuring Technical Efficiency and Technology Gaps in Beef Cattle Production in Argentina," 2015 Conference, August 9-14, 2015, Milan, Italy 211647, International Association of Agricultural Economists.
    6. Phuc Trong Ho & Pham Xuan Hung & Nguyen Duc Tien, 2023. "Effects of varieties and seasons on cost efficiency in rice farming: A stochastic metafrontier approach," Asian Journal of Agriculture and Rural Development, Asian Economic and Social Society, vol. 13(2), pages 120-129.
    7. Juan Cabas Monje & Bouali Guesmi & Amer Ait Sidhoum & José María Gil, 2023. "Measuring technical efficiency of Spanish pig farming: Quantile stochastic frontier approach," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 67(4), pages 688-703, October.
    8. Zarkovic, Maja, 2020. "Cap-and-trade and produce at least cost? Investigating firm behaviour in the EU ETS," Working papers 2020/12, Faculty of Business and Economics - University of Basel.
    9. Li, Hong-Zhou & Kopsakangas-Savolainen, Maria & Xiao, Xing-Zhi & Lau, Sim-Yee, 2017. "Have regulatory reforms improved the efficiency levels of the Japanese electricity distribution sector? A cost metafrontier-based analysis," Energy Policy, Elsevier, vol. 108(C), pages 606-616.
    10. Sebastian Lakner & Thelma Brenes‐Muñoz & Bernhard Brümmer, 2017. "Technical Efficiency in Chilean Agribusiness Industry: A Metafrontier Approach," Agribusiness, John Wiley & Sons, Ltd., vol. 33(3), pages 302-323, June.
    11. Mike Tsionas & Marwan Izzeldin & Arne Henningsen & Evaggelos Paravalos, 2022. "Addressing endogeneity when estimating stochastic ray production frontiers: a Bayesian approach," Empirical Economics, Springer, vol. 62(3), pages 1345-1363, March.
    12. Tom Kompas, 2004. "Market reform, productivity and efficiency in Vietnamese rice production," International and Development Economics Working Papers idec04-4, International and Development Economics.
    13. Hailu, Getu & Goddard, Ellen W. & Jeffrey, Scott R., 2005. "Measuring Efficiency in Fruit and Vegetable Marketing Co-operatives with Heterogeneous Technologies in Canada," 2005 Annual meeting, July 24-27, Providence, RI 19507, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    14. Tanko, Mohammed & Ismaila, Salifu, 2021. "How culture and religion influence the agriculture technology gap in Northern Ghana," World Development Perspectives, Elsevier, vol. 22(C).
    15. Kristof De Witte & Laura López-Torres, 2017. "Efficiency in education: a review of literature and a way forward," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(4), pages 339-363, April.
    16. Economou, Polychronis & Malefaki, Sonia & Kounetas, Konstantinos, 2019. "Productive Performance and Technology Gaps using a Bayesian Metafrontier Production Function: A cross-country comparison," MPRA Paper 94462, University Library of Munich, Germany.
    17. Tsekouras, Kostas & Chatzistamoulou, Nikos & Kounetas, Kostas, 2017. "Productive performance, technology heterogeneity and hierarchies: Who to compare with whom," International Journal of Production Economics, Elsevier, vol. 193(C), pages 465-478.
    18. Bahta, S. & Temoso, O. & Mekonnen, D. & Malope, P. & Staal, S., 2018. "Technical efficiency of beef production in agricultural districts of Botswana: A Latent Class Stochastic Frontier Model Approach," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277207, International Association of Agricultural Economists.
    19. Roengchai Tansuchat, 2023. "A Copula-Based Meta-Stochastic Frontier Analysis for Comparing Traditional and HDPE Geomembranes Technology in Sea Salt Farming among Farmers in Phetchaburi, Thailand," Agriculture, MDPI, vol. 13(4), pages 1-23, March.
    20. Delnava, Haleh & Khosravi, Ali & El Haj Assad, Mamdouh, 2023. "Metafrontier frameworks for estimating solar power efficiency in the United States using stochastic nonparametric envelopment of data (StoNED)," Renewable Energy, Elsevier, vol. 213(C), pages 195-204.

    More about this item

    Keywords

    Livestock Production/Industries;

    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:ags:aesc11:108947. 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: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/aesukea.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.