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Labour allocation patterns of rural households to agriculture and forest activities in Kakamega district, Western Kenya

Author

Listed:
  • Sikei, Geophrey
  • Odhiambo, Mark O.
  • Olwande, John

Abstract

Communities adjacent to forest are faced with a challenge of balancing their labour allocation decisions to the different household activities. This study was done around Kakamega forest in Western Kenya and examined empirically the factors influencing households’ labour allocation to agriculture, forest and non-farm activities. A semi-structured questionnaire was used to collect data from a random sample of 140 households, on household characteristics and key policy parameters affecting labour allocation. A labour share model similar to standard models of commodity or factor demand was used in estimation. The study findings indicate that wage returns on each activity positively influence labour allocation. Additionally education level of household head has a negative influence on forest and non-farm labour shares while positive on agriculture labour share. Other factors like size of landholding and family size all affect household labour allocation decision. These findings have implications for the type of policies needed to support improved labour supply decisions in the rural sector. Investment in livelihood activities in the rural set-up would largely draw much labour to this sector, hence reduced pressure in the forest ecosystems.

Suggested Citation

  • Sikei, Geophrey & Odhiambo, Mark O. & Olwande, John, 2009. "Labour allocation patterns of rural households to agriculture and forest activities in Kakamega district, Western Kenya," 2009 Conference, August 16-22, 2009, Beijing, China 51464, International Association of Agricultural Economists.
    • Handle: RePEc:ags:iaae09:51464
    DOI: 10.22004/ag.econ.51464
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    Cited by:

    1. Nalunga, Asha & Mugisha, Johnny & Walekhwa, Peter & Smith, Jo, 2019. "The dynamics of Household labor allocation to biogas production, farm and non-farm activities in central Uganda," Renewable Energy, Elsevier, vol. 142(C), pages 461-467.

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