ECONOMIC DETERMINANTS OF HOUSEHOLD INCOME FROM FARM GATE DRY MAIZE GRAIN SALES AMONG SMALL-SCALE MAIZE FARMERS IN KEIYO NORTH SUB-COUNTY, KENYA

Abstract

The growth rate in the agricultural sector has been slow in recent times, as shown in the national governments’ bulletins on the performance of various agricultural sub-sectors. Farm gate maize prices have been unstable and sometimes fluctuate to levels too low to cover farmers’ production costs, sparking much debate. This has exposed maize farmers in Keiyo North Sub-County to skewed pricing mechanisms that sometimes work against them. Therefore, this study was conducted to examine the economic Determinants of household income from farm gate dry maize grain sales among small-scale maize farmers in Keiyo North Sub-County, Kenya. The specific objectives were to determine how socioeconomic, marketing, institutional, and pricing factors affect household income among small-scale maize farmers. The study was guided by the Random Utility Maximization (RUM) theory, and both descriptive and cross-sectional research designs were used. Data was collected from a sample of 232 small-scale maize farmers out of a target population of 4,107 farmers, using a multi-stage sampling technique. Data collection was done with questionnaires and analyzed using descriptive and inferential statistics. Multiple Linear Regression was employed to analyze objectives one to four. Descriptive results showed that 46.9% of the small-scale maize farmers were aged 41 to 50 years. About 31.13% had attained primary education. Further, 41.51% had between 5 and 10 years of farming experience. The average land size under maize was 2 acres. The mean annual maize output per acre was 41 bags, with an average of 33 bags sold. The average price of a 90 kg bag of maize was Ksh 2,993. Over half (57.55%) of the farmers belonged to groups, 50.47% had access to extension services, 67.92% did not access credit, and 78.77% had access to market information. The regression analysis on socio-economic factors revealed that age, education level, and land size were statistically significant at the 1% level, with positive coefficients of 0.604, 0.782, and 0.308, respectively. Farming experience was significant at the 5% level with a positive coefficient of 0.329. Marital status and family size were significant at the 5% and 1% levels, with negative coefficients of 0.281 and 0.098, respectively. The analysis of marketing factors indicated that maize output and maize price were significant at the 1% level, with positive coefficients of 0.003 and 0.015. Regarding institutional factors, group membership, credit access, and extension access were significant at the 1% level, with positive coefficients of 2.723, 2.999, and 1.595. Pricing factors showed that maize sales and maize price were significant at the 1% level, with coefficients of 0.001 and 0.018. Access to market information was significant at the 5% level, with a positive coefficient of 0.282. Consequently, the researcher concluded that improving farmer education and strengthening household farming skills through extension services would increase maize production and, ultimately, household income. Additionally, increasing market information would help farmers sell their maize at favorable prices, and allocating more land for maize cultivation could boost output, thereby improving farmers' welfare through higher income. Improving road infrastructure would also help farmers access markets more easily, lower transportation costs, and leave more money in their pockets.