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Optimizing Costs: How Biosecurity Measures Transform Smallholder Poultry Economics

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  • Otieno, Wycliffe A.
  • Nyikal, Rose Adhiambo
  • Mbogoh, Stephen G.
  • Rao, Elizaphan J. O.

Abstract

Attempts to manage poultry diseases through clinical treatment are both costly and increase the risk of antimicrobial resistance (AMR). This study was motivated by the need to tackle the dual challenge of diseases leading to AMR and low poultry productivity in Sub-Saharan Africa. It assesses the cost efficiency of farmers who use varying levels of biosecurity measures. We employ a three-step estimation procedure: first, a latent class analysis (LCA) model to describe adoption patterns. Secondly, a stochastic frontier analysis is used to generate cost efficiency scores and inefficiency effects. Lastly, a one-way ANOVA is used to compare cost efficiency by adoption categories. The LCA model reveals three uptake patterns for biosecurity measures with low, moderate, and high adoption behaviors. The average cost efficiency scores are 49.5%, 61.6%, and 68.6%, respectively, for the low, moderate, and high adoption categories. The overall score of 60.4% indicates that poultry farmers in Nyanza are largely cost-efficient. We demonstrate from the observed pattern that there is room to improve cost performance through increased use of biosecurity measures. Years of experience in poultry farming and larger stock sizes reduce farm cost inefficiency. These findings form the basis for the promotion of biosecurity measures.

Suggested Citation

  • Otieno, Wycliffe A. & Nyikal, Rose Adhiambo & Mbogoh, Stephen G. & Rao, Elizaphan J. O., 2024. "Optimizing Costs: How Biosecurity Measures Transform Smallholder Poultry Economics," IAAE 2024 Conference, August 2-7, 2024, New Delhi, India 344298, International Association of Agricultural Economists (IAAE).
    • Handle: RePEc:ags:cfcp15:344298
    DOI: 10.22004/ag.econ.344298
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    References listed on IDEAS

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    1. Muhammad Arif Watto & Amin W. Mugera, 2014. "Measuring Production and Irrigation Efficiencies of Rice Farms: Evidence from the Punjab Province, Pakistan," Asian Economic Journal, East Asian Economic Association, vol. 28(3), pages 301-322, September.
    2. Amin W. Mugera, 2013. "Measuring technical efficiency of dairy farms with imprecise data: a fuzzy data envelopment analysis approach," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 57(4), pages 501-520, October.
    3. Subal C. Kumbhakar & Mike G. Tsionas, 2021. "Estimation of costs of technical and allocative inefficiency," Journal of Productivity Analysis, Springer, vol. 55(1), pages 41-46, February.
    4. Sreejith Aravindakshan & Frederick Rossi & T. S. Amjath-Babu & Prakashan Chellattan Veettil & Timothy J. Krupnik, 2018. "Application of a bias-corrected meta-frontier approach and an endogenous switching regression to analyze the technical efficiency of conservation tillage for wheat in South Asia," Journal of Productivity Analysis, Springer, vol. 49(2), pages 153-171, June.
    5. Marc F. Bellemare & Casey J. Wichman, 2020. "Elasticities and the Inverse Hyperbolic Sine Transformation," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(1), pages 50-61, February.
    6. Timothy J. Coelli & D.S. Prasada Rao & Christopher J. O’Donnell & George E. Battese, 2005. "An Introduction to Efficiency and Productivity Analysis," Springer Books, Springer, edition 0, number 978-0-387-25895-9, June.
    7. Battese, G E & Coelli, T J, 1995. "A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data," Empirical Economics, Springer, vol. 20(2), pages 325-332.
    8. Battese, George E. & Coelli, Tim J., 1988. "Prediction of firm-level technical efficiencies with a generalized frontier production function and panel data," Journal of Econometrics, Elsevier, vol. 38(3), pages 387-399, July.
    9. Theo Stratopoulos & Evangelos Charos & Kelly Chaston, 2000. "A translog estimation of the average cost function of the steel industry with financial accounting data," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 6(2), pages 271-286, May.
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    Keywords

    Farm Management; Food Consumption/Nutrition/Food Safety;

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