A Linear Regression Model For Predicting The Level Of Need For Social Protection In Kenya

Abstract

This research delved into the complex dynamics of social disadvantage in Kenya, focusing on the nation's unique social protection needs. Using the Kenya Integrated Household Budget Survey (KIHBS), we explored factors such as Household income, Educational Attainment, Employment status, Health Indicators, and Disability Status. The research findings identified household income and disability status as crucial determinants for social disadvantage, underlining the importance of fair economic opportunities. Education and employment also emerged as significant influences, emphasizing the need for comprehensive educational access and robust job creation strategies. Based on the linear regression model statistics, the R-square value of 0.656 showed a stable model. Other regression validation metrics such as residual errors helped to confirm this. The study recommends refining data consolidation techniques to uncover deeper disparities within Kenya's diverse population. While highlighted key social disadvantage determinants have been highlighted, a more detailed examination of the urban-rural divide is essential. The study, deeply rooted in theoretical frameworks, suggests that further research should explore how these theories tangibly relate to the experiences of Kenyans, providing a foundation for creating more inclusive societies both in Kenya and globally.