IDEAS home Printed from https://ideas.repec.org/a/taf/applec/v51y2019i26p2855-2871.html
   My bibliography  Save this article

How efficient is maize production among smallholder farmers in Zimbabwe? A comparison of semiparametric and parametric frontier efficiency analyses

Author

Listed:
  • Xiaoli L. Etienne
  • Giancarlo Ferrara
  • Douglas Mugabe

Abstract

The controversial Fast Track Land Reform Programme in Zimbabwe that redistributes commercially-owned farmland to smallholder households has caused concerns about the efficiency of agricultural production in the country. In this paper, we estimate the efficiency of resource use among smallholder farmers in Zimbabwe when producing maize, the staple crop in the country. Using both a semiparametric model and a fully parametric stochastic frontier model, we find significant production shortfalls for smallholder maize production. While labor, capital, and land all significantly affect the total output, the estimated mean efficiency score for farms with less than 10 hectares of land (A1) appears to be under 0.75, and for the entire sample (A1 and A2) it ranges between 0.595 and 0.772. There clearly exists a great potential for maize farmers to improve the technical efficiency and increase the total output. Gender and age of the household head, access to extension services, and activities of other crops significantly affect the technical efficiency of smallholder maize production in Zimbabwe. We also find that all farms operate under increasing returns to scale and that the technical efficiency score tends to increase with the level of output.

Suggested Citation

  • Xiaoli L. Etienne & Giancarlo Ferrara & Douglas Mugabe, 2019. "How efficient is maize production among smallholder farmers in Zimbabwe? A comparison of semiparametric and parametric frontier efficiency analyses," Applied Economics, Taylor & Francis Journals, vol. 51(26), pages 2855-2871, June.
    • Handle: RePEc:taf:applec:v:51:y:2019:i:26:p:2855-2871
    DOI: 10.1080/00036846.2018.1558363
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/00036846.2018.1558363
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/00036846.2018.1558363?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Elton G. Aráujo & Julio C. S. Vasconcelos & Denize P. Santos & Edwin M. M. Ortega & Dalton Souza & João P. F. Zanetoni, 2023. "The Zero-Inflated Negative Binomial Semiparametric Regression Model: Application to Number of Failing Grades Data," Annals of Data Science, Springer, vol. 10(4), pages 991-1006, August.
    2. Federico Belotti & Giancarlo Ferrara, 2019. "Imposing monotonicity in stochastic frontier models: an iterative nonlinear least squares procedure," CEIS Research Paper 462, Tor Vergata University, CEIS, revised 29 Jan 2021.
    3. Fujia Sui & Yinsheng Yang & Shizhen Zhao, 2022. "Labor Structure, Land Fragmentation, and Land-Use Efficiency from the Perspective of Mediation Effect: Based on a Survey of Garlic Growers in Lanling, China," Land, MDPI, vol. 11(6), pages 1-17, June.

    More about this item

    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:taf:applec:v:51:y:2019:i:26:p:2855-2871. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/RAEC20 .

    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.