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|Title:||Determinants of schooling returns; a case study of employees of Atutur Hospital in Kumi district:|
|Publisher:||Kampala International University, College of Economics and Management.|
|Abstract:||This study mainly focused on investigating the relationship between schooling and the earnings (wages) of the health workers. A case study was carried on employees of Atutur referral hospital in Kumi district in Eastern Uganda. The study specific objectives were to find out the level of earnings of health workers, determine the relationship between years of schooling, age, and experience and education level on employee earnings. And finally to investigate the effect of years of schooling, age, experience and education level on earnings of employees. The researcher investigated the relationship between years of schooling, age and experience by carrying out correlations on earnings and testing hypothesis using the t sampling statistics. However since education was a categorical variable the researcher used the one way ANOVA and test hypothesis for statistical difference in means earnings of each education level. To investigate the effect of years of schooling, age, and experience and education level on earnings, the researcher used the Mincerian OLS regression model that regresses the natural logarithm of earnings of employees and this effect tested using the F statistic. The Pearson correlation coefficients sig. (2tailed) yielded correlation coefficients of 0.54 for years of schooling, -0.208 for age and -0.267. One way ANOVAF ((2, 79) =54.664, p=O.003) showed at least there was significant differences in mean earnings of each education levels, at 0.05 level and a Tukey post hoc test for multiple comparison of mean earnings of each education level showed that this mean differences were statistically significantly higher on tertiary levels (13.19±0.713, pO.000) compared to primary level (11.12±0.522, p=O.5O8) and secondary (11.47±0.818, p0.SOS). This showed a no statistical significant difference in mean earnings of primary and secondary education level. The results also showed earnings rise with education level. A secondary education added a 0.35 mean earnings on primary level and a tertiary level added a 1.72 mean earnings to secondary schooling. Regression at 95% confidence level yielded regression coefficients of 0.0 19 for years of schooling, 0.028 for age, -0.015 for experience and -1.6348 for primary education and -0.9432 on secondary education (regression coefficients for education taken for dummies of ‘0’ and ‘1’ tertiary education was used as a reference group. The researcher observed that earnings were significantly dependent on years of schooling, age and experience and education level. It was also observed that earnings were significantly lower for primaryand secondary education in comparison to the other group (tertiary education) and the wage gap was statistically significant. Experience had nonlinear relationships on earnings. The researcher attributes the experience effect on ability and specialization effect. Specialization causes mismatch in job requirements. Some employees can be too specialized which cuts them from some job requirements due to over experience. When the effects were tested the researcher noticed that variation in earnings was explained by the independent variables used. The researcher recommends further research on experience and earnings effect for future academicians they can as well investigate returns to schooling and poverty. Government needs to adopt policies that maintain children at school, and as well adopt proper subsidization policy for higher levels of education to enable scholars enrich their schooling potentials. On wage issue, the research advises government to adopt a salary review team to review salaries and create equal opportunities of wages for employees of similar qualifications. Government should too adopt cost sharing with investors in aspects likes employee training. By reducing labour training costs, employees have a chance of being selected and enjoy balanced earnings.|
|Description:||dissertation summited to the college of economics and management department of economics and applied statistics in partial fulfillment for the award of the degree of bachelor of economics v and applied statistics of Kampala international university.|
|Appears in Collections:||Bachelors Degree in Economics|
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