The Socio-Economic Factors Affecting Dry Maize Grain Output on Household Income Among Small-Scale Maize Farmers in Keiyo North, Elgeyo Marakwet County

Author: Andrew Kibet Yano, Dr. Elijah Ngeno

Date: 2025

Abstract: The growth rate in the agricultural sector has been slow in recent times as captured in the national governments’ bulletins on performances by various agricultural sub-sectors. Farm gate maize prices have been unstable and sometimes fluctuating to levels too low to cover farmers’ production costs, eliciting much debate. This has exposed maize farmers in Keiyo North SubCounty to skewed pricing mechanisms which sometimes work to their disadvantage. Therefore, this study was carried out in Keiyo North Sub-County, Elgeyo Marakwet County with the objective of analysing the Socio-Economic Factors Affecting Dry Maize Grain Output on Household Income Among Small-Scale Maize Farmers in Keiyo North, Elgeyo Marakwet County. The study was guided by Random Utility Maximization (RUM) theory and descriptive and cross-sectional research designs were adopted. Data was collected from a sample of 232 small-scale maize farmers from a target population of 4,107 farmers using multi-stage sampling technique. Data for the study was collected using a questionnaire and analysed using descriptive and inferential statistics. Multiple Linear Regression model was used to analyse objectives one to four with the help of the Stata software. Descriptive results revealed that 46.9% of the smallscale maize farmers were aged 41 to 50 years. 31.13% of the small-scale maize farmers had attained primary-level education. Further, results showed that 41.51% of the small-scale maize farmers had between 5 to 10 years in maize farming. The mean land size under maize farming was 2 acres. Results further, revealed that the average annual maize output per acre was 41 21 bags, the average number of bags sold was 33, while the mean price of a 90 kg bag of maize was Ksh 2,993. Moreover, 57.55% of the small-scale maize farmers belonged to groups, 50.47% of the farmers had access to extension services, 67.92 did not access credits, and 78.77%accessed market information. Multiple Linear Regression estimates on the effects of socio-economic determinants on household income results revealed that age, education level, and land size were statistically significant at 1% level with 0.604, 0.782, and 0.308 positive coefficients, respectively.

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