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Allocative and scale efficiency among maize farmers in Zambia: a zero efficiency stochastic frontier approach

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  • Abdul Nafeo Abdulai
  • Awudu Abdulai

Abstract

The commonly used stochastic frontier model assumes that all firms are inefficient. In this specification, inefficiency is non-negative, and the probability of inefficiency being exactly zero is also zero. To the extent that efficiency varies widely across farms in under-developed economies, it is important to employ techniques that account for both inefficiency and full efficiency to ensure unbiased efficiency estimates. In this study, we employ a zero-inefficiency stochastic frontier model to examine allocative efficiency and scale economies, as well as key determinants of efficiency among Zambian maize farmers. The results show that, unlike the stochastic frontier model, the zero-inefficiency stochastic frontier model successfully allows for both fully efficient and inefficient firms to be accounted for in the estimation procedure. The estimates also reveal the presence of scale economies, with the zero-inefficiency stochastic frontier model better predicting scale efficiency compared to the stochastic frontier model. The findings also show that inefficiency is explained by the level of education, access to extension services, distance to markets and access to credit.

Suggested Citation

  • Abdul Nafeo Abdulai & Awudu Abdulai, 2016. "Allocative and scale efficiency among maize farmers in Zambia: a zero efficiency stochastic frontier approach," Applied Economics, Taylor & Francis Journals, vol. 48(55), pages 5364-5378, November.
  • Handle: RePEc:taf:applec:v:48:y:2016:i:55:p:5364-5378
    DOI: 10.1080/00036846.2016.1176120
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    References listed on IDEAS

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    1. World Bank, 2009. "Awakening Africa's Sleeping Giant : Prospects for Commercial Agriculture in the Guinea Savannah Zone and Beyond [Le réveil du géant assoupi : Perspectives de l’agriculture commerciale dans les sava," World Bank Publications - Books, The World Bank Group, number 2640.
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    Cited by:

    1. T. O. Ojo & A. A. Ogundeji & S. C. Babu & T. Alimi, 2020. "Estimating financing gaps in rice production in Southwestern Nigeria," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 9(1), pages 1-18, December.
    2. Asante, Bright O. & Temoso, Omphile & Addai, Kwabena N. & Villano, Renato A., 2019. "Evaluating productivity gaps in maize production across different agroecological zones in Ghana," Agricultural Systems, Elsevier, vol. 176(C).
    3. Awudu Abdulai, 2018. "Simon Brand Memorial Address," Agrekon, Taylor & Francis Journals, vol. 57(1), pages 28-39, January.
    4. John N. Ng’ombe, 2017. "Technical efficiency of smallholder maize production in Zambia: a stochastic meta-frontier approach," Agrekon, Taylor & Francis Journals, vol. 56(4), pages 347-365, October.
    5. Lin, J. & Z. & Zhang, Z., 2018. "Does transportation matter to tobacco leaf producers? Evidence from Guizhou, China," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 276998, International Association of Agricultural Economists.
    6. Dénis B. Akouwerabou, 2023. "Effect of agricultural extension on cotton farmer's efficiency in arid and semi‐arid areas of Burkina Faso," Natural Resources Forum, Blackwell Publishing, vol. 47(1), pages 42-59, February.
    7. Ngango, Jules & Seungjee, Hong, 2021. "Examining the Relationship between Farm Size and Technical Efficiency in Rwandan Maize Production," 2021 Conference, August 17-31, 2021, Virtual 314937, International Association of Agricultural Economists.
    8. Zainab Oyetunde-Usman & Kehinde Oluseyi Olagunju, 2019. "Determinants of Food Security and Technical Efficiency among Agricultural Households in Nigeria," Economies, MDPI, vol. 7(4), pages 1-13, October.

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