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Autoregressive Distributed Lag Modeling Of Impact Of Climatic And Non-Climatic Factors Influencing Sorghum Production In Ethiopia

Author

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  • Abera Gayesa Tirfi

    (Addis Ababa, ETHIOPIA)

Abstract

This study examined factors influencing sorghum output in Ethiopia using ARDL model over the period 1981 to 2020. The elasticity coefficient of crop growing period mean temperature showed negatively significant impact on sorghum production in the long-run, aligning with theory. Conversely, main-season rainfall had positively significant impact on sorghum output, contrasting with the theory. Among non-climatic variables, sorghum price and area under sorghum had affirmatively considerable contribution to sorghum production as expected in theory. In the short-run, mean temperature revealed negatively significant impact on sorghum production, supporting the theory. Conversely, the main season rainfall and area under sorghum production demonstrated positively significant impact on sorghum production. Furthermore, sorghum output is positively responsive to own price during the second lag differences, implying that any price incentive strategy should be released before the last year. Equally, sorghum output is positively responsive to fertilizers applied in the first lag, which implies that fertilizers applied on sorghum cultivation during first lag difference have positive contribution to sorghum output supply. In view of the results of the current study, it is strongly recommended that the government should come up with strategies and policies that help sorghum farmers to mitigate and adapt to climate change.

Suggested Citation

  • Abera Gayesa Tirfi, 2023. "Autoregressive Distributed Lag Modeling Of Impact Of Climatic And Non-Climatic Factors Influencing Sorghum Production In Ethiopia," Malaysian Journal of Sustainable Agriculture (MJSA), Zibeline International Publishing, vol. 7(1), pages 52-57, March.
  • Handle: RePEc:zib:zbmjsa:v:7:y:2023:i:1:p:52-57
    DOI: 10.26480/mjsa.01.2023.52.57
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    References listed on IDEAS

    as
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