Determinants of Objective and Subjective Poverty in Kenya: Evidence from Kiambu County, Kenya

Many Sub-Saharan African countries, including Kenya, continue to grapple with high levels of poverty. While research on poverty has advanced considerably, it remains heavily reliant on monetary indicators such as household income or consumption expenditure. However, there is growing concern about the adequacy of these metrics, given the variation in individual needs and preferences. This study explores an alternative approach: measuring poverty through households' subjective perceptions of their economic well-being. A cross-sectional survey research design was employed in Kiambururu and Komothai locations of Githunguri sub-county, Kiambu County, Kenya. A multi-stage sampling technique was used to select a representative sample of 202 smallholder farming households. Both descriptive and inferential statistical methods were applied. Descriptive statistics included frequencies, percentages, means, and standard deviations, while ordered logistic regression and binary logistic regression were used to examine the determinants of subjective and objective poverty, respectively. The study found that 32.2% of respondents considered themselves to be "just getting along." Subjective poverty was less likely among households with higher income, savings, more educated household heads, and at least one member employed in either the formal or informal sector. In contrast, larger household sizes increased the likelihood of perceiving poverty. Objective poverty, defined by the national poverty line of Ksh 3,947 per person per month (in adult equivalent terms), affected 46.04% of the households. Households with more frequent income inflows and larger sizes were more likely to be objectively poor. Conversely, male-headed households and those with the ability to save were less likely to fall below the poverty line. The findings underscore the importance of complementing traditional poverty metrics with subjective assessments. Individuals living in poverty are often the best judges of their own well-being. For improved policy formulation and targeting, triangulating objective measures with subjective perceptions offers a more comprehensive understanding of poverty. A correction factor should be integrated into poverty measurement methodologies to bridge the gap between statistical indicators and lived realities.