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Farm level allocative efficiency of rice production in Gulu and Amuru districts, Northern Uganda

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  • Daniel Micheal Okello

    (Gulu University)

  • Jackline Bonabana-Wabbi

    (Makerere University)

  • Basil Mugonola

    (Gulu University)

Abstract

Smallholder farming, predominant in Uganda, is characterized by low productivity for most crops including rice which is gaining prominence as both a food and income crop. The low productivity is mostly attributed to allocative inefficiency. Allocative efficiency (AE) considers farmers’ ability to allocate resources efficiently, by producing the maximum possible output at minimum cost. Increasing AE requires an understanding of the specific sources of inefficiency that vary across farm enterprises, geographically and temporally. A cross-sectional study was carried out in Gulu and Amuru districts of Northern Uganda to assess the sources of farm-level allocative inefficiency in rice production using the stochastic frontier approach. Data were collected from a random sample of 200 smallholder rice farmers. Results show that the mean AE was 75%. Household size, distance to trading centre, farm size, number of crop enterprises, use of hired labour, use of ox-plough, and access to credit had significant effects on AE. We recommend adoption of technologies such as the use of ox-ploughs and reallocation of farm resources especially labour.

Suggested Citation

  • Daniel Micheal Okello & Jackline Bonabana-Wabbi & Basil Mugonola, 2019. "Farm level allocative efficiency of rice production in Gulu and Amuru districts, Northern Uganda," Agricultural and Food Economics, Springer;Italian Society of Agricultural Economics (SIDEA), vol. 7(1), pages 1-19, December.
    • Handle: RePEc:spr:agfoec:v:7:y:2019:i:1:d:10.1186_s40100-019-0140-x
    DOI: 10.1186/s40100-019-0140-x
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    2. Francisca Ndinda Muteti & Irine Akite & Taddias Prince Mpofu & Basil Mugonola, 2024. "Determinants of technical efficiency among smallholder upland rice farmers in northern Uganda—a Cobb–Douglas stochastic frontier approach," SN Business & Economics, Springer, vol. 4(1), pages 1-20, January.
    3. Twecan, Dalson & Wang, Weiguang & Xu, Junzeng & Mohmmed, Alnail, 2022. "Climate change vulnerability, adaptation measures, and risk perceptions at households level in Acholi sub-region, Northern Uganda," Land Use Policy, Elsevier, vol. 115(C).
    4. Midamba Dick Chune & Mustaf Mohamed Takoy & Odongkara Peter, 2022. "Analysis of technical efficiency and its determinants among tobacco producers in Uganda: An application of data envelopment analysis," International Journal of Agricultural Research, Innovation and Technology (IJARIT), IJARIT Research Foundation, vol. 12(1), June.
    5. Radha R. Ashrit, 2023. "Estimation of technical efficiency of Indian farms for major crops during 2013–2014 and 2017–2018: a stochastic Frontier production approach," SN Business & Economics, Springer, vol. 3(2), pages 1-32, February.

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