EFFECTS OF FARMER SOCIO-DEMOGRAPHIC FACTORS ON AGRICULTURAL PROJECTS IN KENYA: A CASE OF NARIG PROJECT IN MAKUENI COUNTY
EFFECTS OF FARMER SOCIO-DEMOGRAPHIC FACTORS ON AGRICULTURAL PROJECTS IN KENYA: A CASE OF NARIG PROJECT IN MAKUENI COUNTY
Daniel Mutinda Muli Ksee - Student, Master of Arts in Public Policy and Administration, Kenyatta University, Kenya
Patrick Mbataru - Lecturer, Department of Public Policy and Administration, Kenyatta University, Kenya
ABSTRACT
Agriculture significantly influences food security and economic progress at a global scale. Many developing countries including Kenya invest in agriculture towards rural development and poverty alleviation. In this investment, most countries work through agriculture development projects which are expected to produce results. Literature on assessment of performance of agricultural development projects tend to focus on the project cycle. There is little literature on the role of the farmer in the performance of these projects, yet they are key to the success of the projects. To fill in the missing gaps, this study aims at assessing the performance of the NARIGP, a five-year project funded by the World Bank that has been carried out by the Kenyan government in 21 out of 47 counties in Kenya including Makueni County where it is implemented in 20 out of 30 wards across the six sub-counties. The project's overarching goal is to boost agricultural productivity and profitability, which will subsequently enhance livelihoods and lessen vulnerabilities in the selected counties' targeted rural populations. The study will be in Makueni County. The study utilized the Agrarian change theory by Boserup and the theory of planned behavior as theoretical frameworks of the research. The research employed a descriptive survey design. The target population was the 18,754 farmers who have been implementing the project. A stratified and purposive sampling design was used to select 392 respondents, a sample size determined using sample size determination table recommended by (Naing, 2003), a structured questionnaire was used with the data being collected by research assistants to an online tool for analysis using inferential and descriptive statistics. Descriptive statistical analysis used percentages, means and frequencies while inferential statistical analysis used Pearson correlation and linear regression. Correlation analysis showed that farmer attitude; farmer knowledge and farmer practices are strong determinants of project performance while there was very little correlation between demographic factors and the performance of the project. Further statistical analysis (ANOVA, T-test and Linear regression) showed that gender, level of education, household size, monthly income, experience in the value chain and age were found to play no significant role in the performance of the project while the ward, family headship and chosen value chain were found to play some significant role. Farmer’s attitude, knowledge and practices were found to influence the performance of the project. The study recommends that project formulation should consider these factors to enhance success.
