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Analysis on returns to levels of education and challenges faced by the urban self employed in Kisii county, Kenya

Show simple item record NYAKUNDI, Eliud 2019-01-16T13:25:50Z 2019-01-16T13:25:50Z 2018
dc.description.abstract The self-employment sector provides an avenue for workers to earn a living. The returns to the self-employed remains unexplained. Studies in Britain, United States of America, Tunisia Tanzania, Ghana and Tanzania among others studies cited mixed findings on the relationship between returns to education and levels of education. In Kenya studies indicate the increasing entry of school graduates of all levels of education entering the self-employment whose returns remains unpredictable. In Kisii County there are worker entering into employment in computer and motor spare parts with various levels of education whose returns have not been adequately investigated. The purpose of the study was to determine education returns to computer and spare parts self-employment activities in urban Kisii County. The study objectives were to; analyze the returns to levels of education of the self-employed in computer industry, analyze the returns to education of levels of education of the self-employed in spare parts industry, analyze the challenges facing the self-employed in computer service and motor spare industries, analyze effectiveness of intervention measures by Kenya government to support the self-employed in their work. The study used descriptive and correlation design. The study used human capital theory as advanced by Becker which states that earnings rise with additional years of schooling. The population of the study was 11,240. That is in computer service industry 6,400 and spare parts 4840 workers. The study used Glen model to derive a sample of 384 respondents with 218 computer services and 166 spare parts self-employed workers. Questionnaire and interview schedules were used to collect data for the study. Validation of the instruments was done by consultation with supervisors of this study and other researchers to ensure they complied with universal standard of proposal and research finding reporting. Reliability of instruments was established at 0.7. Quantitative data was analyzed using descriptive statistics and inferential statistics. Qualitative data was transcribed and analyzed in emergent themes and sub-themes and reported verbatim. The study found out that; on average in computer service industry self-employed respondents with KCPE, K.C.S.E and diploma had similar amount of returns while bachelor’s degree and masters earnings were higher with certificate recording lower earnings. The Pearson’s r results were’ KCPE 0.643, KCSE 0.104, certificate 0.128, diploma 0.195 and bachelor’s degree 0.045. Respondents with K.C.P.E level of education had higher returns than those with K.C.S.E and diploma. The r2 analysis was: KCPE category the r2 was 0.0413, KCSE was 0.011, certificate 0.016, and diploma was 0.038 for bachelors. The adjusted R results were: KCPE 0.373, KCSE 0.02, certificate 0.002, diploma 0.001 and bachelors 0.075. The ANOVA indicated KCPE (F (1, 15) 10.572, P = 0.005), while other levels were moderate at KCSE was (F (1, 70) 0,761, P=0.386), certificate was (F (1, 52,) = 0.868, P = 0.356), diploma was (F (1, 28) =1.031, P=0.319 and bachelor results were (F (1,13)=0.006, P = 0.874). The combined levels of education explained 22.6% of the returns in education. The result therefore indicated that education levels marginally explain the returns to education in computer service industry. In spare parts the results showed that on average; respondents with KCPE, KCSE and certificate earned nearly similar amount of money. Diploma graduates earnings bachelor’s degree and masters graduates recorded higher earnings. Analysis of Pearson’s r indicated that; KCPE was 0.617, KCSE 0.009, certificate 0.130, diploma 0.129 and bachelors 0.297. The Pearson’s r2 results were: KCPE as 0.413, KCSE 0.011, certificate 0.016, diploma 0.038 and degree 0.002. The adjusted R results were: KCPE 0.373. KCSE 0.002, certificate 0.002, diploma 0.001 and degree 0.075. The ANOVA results were: for KCPE (F (1,20)=12.282, P=0.002), while the rest were moderate at KCSE (F (1,84)=0,007, P=0.935), certificate was (F (25,)=0.428, P=0.519), diploma was (F (1,17)=1.290, P=0.597) and bachelor’s degree was (F (1,10)=0.0.964, P=0.349). The combined effects of all levels of education explained 31.8% while 68.2% remained unexplained. Education levels therefore significantly explained the returns to education. Government intervention were not effective in the provision of: market stalls, loans and market for finished products, but effective in provision of: security, electricity and infrastructure. The study conclude that K.C.P.E level of education had positive returns and other levels of education could not be relied upon to explain the returns to education. The study recommended curriculum review in other levels of education apart from K.C.P.E to make them relevant to the needs of the self-employed in computer and motor spare part. The study is important in formulation of education programmes relevant to the self-employed and government intervention in support of the self-employed. en_US
dc.language.iso en_US en_US
dc.publisher Maseno University en_US
dc.subject Planning and economics of education en_US
dc.title Analysis on returns to levels of education and challenges faced by the urban self employed in Kisii county, Kenya en_US
dc.type Thesis en_US

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