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Stochastic maize production technology and production risk analysis in Dadar district, East Ethiopia

  • Fufa, B.
  • Hassan, Rashid M.
Registered author(s):

    A stochastic production technology that allows risk effects of factor inputs was estimated for maize farmers in Ethiopia. The results suggested that the promoted improved maize technology exhibits constant returns to scale whereas non-adopters use decreasing returns to scale technology. The study showed that timely planting is critical for maize yield stability among both adopters and non-adopters and suggests the importance of using oxen and higher efforts to achieve that. Nevertheless, the results showed that most of the factors under the control of the farmers do not offer powerful explanation to maize yield variability compared to natural factors such as rainfall, frost, pests and diseases.

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    File URL: http://purl.umn.edu/9507
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    Article provided by Agricultural Economics Association of South Africa (AEASA) in its journal Agrekon.

    Volume (Year): 42 (2003)
    Issue (Month): 2 (June)
    Pages:

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    Handle: RePEc:ags:agreko:9507
    Contact details of provider: Web page: http://www.aeasa.org.za/
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    1. R. M. Hassan & A. Hallam, 1990. "Stochastic Technology In A Programming Framework: A Generalised Mean-Variance Farm Model," Journal of Agricultural Economics, Wiley Blackwell, vol. 41(2), pages 196-206.
    2. Antle, John M, 1983. "Testing the Stochastic Structure of Production: A Flexible Moment-based Approach," Journal of Business & Economic Statistics, American Statistical Association, vol. 1(3), pages 192-201, July.
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