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What drives diversity in climate change adaptation strategies for African indigenous vegetable production in Kenya?

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  • Chepkoech, Winifred
  • Stöber, Silke
  • Kurgat, Barnabas K.
  • Bett, Hillary K.
  • Mungai, Nancy W.
  • Lotze-Campen, Hermann

Abstract

Smallholder farmers have adopted diverse adaptation practices to lessen the effect of climate change. However, context-specific information about why particular adaptation strategies are adopted remains limited. This study examined the factors that facilitate the choice of farm-level adaptation strategies to climate change (CC) using data collected from 269 African indigenous vegetable (AIV) farmers in Kenya. A multivariate probit (MVP) regression model was used to evaluate the determinants of adaptation choices. The most frequently adopted strategies considered for analysis were manure application, increased pesticide use, crop rotation, irrigation, change of planting dates and terracing. The results reveal that land ownership, group membership, access to extension services and education level were some of the key drivers of adoption. This implies that policies and programmes that are designed to build the ability of smallholder AIV farmers to adapt to climate change should focus on organising farmers into groups, disseminating timely weather information, improving land tenure security, increasing off-farm employment and providing greater access to extension services.

Suggested Citation

  • Chepkoech, Winifred & Stöber, Silke & Kurgat, Barnabas K. & Bett, Hillary K. & Mungai, Nancy W. & Lotze-Campen, Hermann, 2023. "What drives diversity in climate change adaptation strategies for African indigenous vegetable production in Kenya?," Economic Analysis and Policy, Elsevier, vol. 77(C), pages 716-728.
    • Handle: RePEc:eee:ecanpo:v:77:y:2023:i:c:p:716-728
    DOI: 10.1016/j.eap.2022.12.016
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    1. Chandio, Abbas Ali & Ozdemir, Dicle & Jiang, Yuansheng, 2023. "Modelling the impact of climate change and advanced agricultural technologies on grain output: Recent evidence from China," Ecological Modelling, Elsevier, vol. 485(C).

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