Factors Affecting Adaptation to Climate Change through Agroforestry in Kenya

Kevin Pello, Cedric Okinda, Aijun Liu and Tim Njagi
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Kevin Pello: College of Economics and Management, Nanjing Agricultural University, Nanjing 210095, China
Cedric Okinda: Laboratory of Modern Facility Agriculture Technology and Equipment Engineering of Jiangsu Province, College of Engineering, Nanjing Agricultural University, Nanjing 210031, China
Aijun Liu: College of Economics and Management, Nanjing Agricultural University, Nanjing 210095, China
Tim Njagi: Tegemeo Institute of Agricultural Policy and Development, Egerton University, P.O. Box 20498-00200 Nairobi, Kenya
Authors registered in the RePEc Author Service: Timothy Njagi Njeru

Land, 2021, vol. 10, issue 4, 1-16

Abstract: The environmental effects of climate change have significantly decreased agricultural productivity. Agroforestry technologies have been applied as a solution to promote sustainable agricultural systems. This study evaluates the factors influencing the adoption of agroforestry technology in Kenya. A multistage sampling technique was employed to collect data from 239 households in West Pokot County, Kenya. A Probit model and K- means algorithm were used to analyze the factors affecting farmers’ agroforestry technology adoption decisions based on the sampled households’ socio-economic, demographic, and farm characteristics. The study found that the total yield for maize crop, farm size, extension frequency, off-farm income, access to training, access to credit, access to transport facilities, group membership, access to market, gender, distance to nearest trading center, and household education level had significant effects on the adoption of agroforestry technologies. The findings of this study are important in informing policy formulation and implementation that promotes agroforestry technologies adoption.

Keywords: climate change; agroforestry-based technology; probit model; K- means (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2021
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