Estimating Sub-County Literacy Rates in Kenya’s Coastal Region Using the Fay–Herriot Model

Reliable literacy estimates at lower administrative levels are essential for identifying educational inequalities and informing evidence-based planning. However, national household surveys are typically designed to generate reliable estimates at national and county levels, resulting in unstable direct estimates for smaller domains such as sub-counties. This study aimed to estimate sub-county literacy rates in Kenya’s Coastal Region using the Fay–Herriot area-level small area estimation model and to examine the spatial distribution and precision of the resulting estimates. Literacy data were obtained from the 2022 Kenya Demographic and Health Survey, while auxiliary variables were derived from the 2019 Kenya Population and Housing Census. Direct literacy estimates and their sampling variances were first computed for each sub-county. A Fay–Herriot model was then fitted using three selected auxiliary variables: the proportion of persons living in urban areas, the proportion in the lower wealth category, and the proportion with basic education and above. The model generated literacy estimates for 29 sub-counties, which were subsequently mapped to assess geographic variation and estimate reliability. The results revealed substantial spatial variation in literacy levels across the Coastal Region. Higher literacy estimates were observed in Mvita, Voi, Changamwe and Mwatate, while lower estimates were recorded in Tana Delta, Tana North and Lunga Lunga. The Fay–Herriot model improved estimate precision, with most relative standard errors falling below 10%, indicating acceptable reliability for small-area statistics. However, estimates for Tana North, Tana Delta and Tana River exhibited comparatively higher uncertainty and should be interpreted with caution. The study concludes that the Fay–Herriot model provides reliable sub-county literacy estimates by combining survey and census information, thereby supporting more targeted educational planning and resource allocation in Kenya’s Coastal Region.

Fay–Herriot model, Literacy Estimation, Small Area Estimation, Kenya

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