TABLE OF CONTENTS
DECLARATION
APPROVAL
DEDICATION
ACKNOWLEDGEMENT iv
ABSTRACT V
LIST OF ACRONYMNS Vii
TABLE OF CONTENTS Viii
LIST OF TABLES XH
CHAPTER ONE 1
INtRODUCTION 1
1.0 Introduction 1
1.1 Background of the Study 1
1.3 Statement of the Problem 5
1.4 Main Purpose of the Study 6
1.5 Objectives of the Study 6
1.6 Research Questions 6
1 .7Research Hypotheses 7
1.8 Scope of the Study 7
1.8.1 Geographical Scope
1.8.2 Content Coverage 7
1.9 Significance of the Study 7
VIII
CHAPTER TWO
LITERATURE REVIEW 9
2.1 Introduction 9
2.2 Theoretical Literature Review 9
2.3 Conceptual Framework 12
2.4 Empirical Literature Review 12
CHAPTER THREE 15
RESEARCH METHODOLOGY 15
3.0 Introduction 15
3.lDatatype 15
3.1.1 Econometric model selection and Specification 15
3.2.2 Data Source 16
3.2.4 Target Population 16
3.2.5 Sample size 17
3.2.6 Sampling Design 17
3.3 Data Collection Instrument and field work 17
3.3.1 Data Collection Instrument 17
3.3.2 Data Collection Procedures 18
3.4 Data Processing 18
3.5 Data Analysis 18
ix
CHAPTER FOUR .19
PRESENTATION AND ANALYSIS OF FINDINGS 19
4.1 Introduction 19
4.2 Demographic Characteristics of the Survey Respondents 19
4.3 Descriptive Statistics of Employee Level of earnings and Schooling characteristics .20
4.4 The Relationship between Years of Schooling, Age, Experience and Education level
on Employee Earnings 21
4.4.1 Correlation between Years of Schooling and Earnings (wage) of the Employees...21
4.4.2 Age and the Earnings of the Employees 22
4.4.3 Experience and Earnings of the Employees 22
4.4.4 Education and Employee Earnings (wage) 23
4.5 The Effect of Years of Schooling, Age, Experience and Education level on Earnings
of employees 25
4.5.1 Goodness of fit of the model used in regression analysis 27
CHAPTER FIVE 28
DISCUSSION OF FINDINGS, CONCLUSION AND RECOMMENDATION 28
5.1 Summary of Findings 28
5.1.1 Demographic Characteristics of respondents 28
5.1.2 Description of the Schooling and earning levels of the employees 28
5.1.3 The relationship between years of schooling, age, experience and education level on
earnings of the employees 29
5.1.3.1 Years of Schooling and employee earnings 29
5.1.3.2 Age and employee earnings 29
5.1.3.3 Experience and earnings of the employees 29
5.1.3. Education level and earnings of the employees 30
x
5.1.4 The effect of years of schooling, age, experience and education level on employee
Earnings 30
5.1.4.2 Justification of Goodness of fit of the regression model used 31
5.1.5 Discussions and Conclusions 31
5.2 Recommendations 32
REFERENCES
APPENDICES 36
APPENDIX 1: LETTER OF PERMISSION TO CONDUCT RESEARCH 36
APPENDIX 2: QUESTIONNAIRE DESIGN 37
APPENDIX 3: CURRICULUM VITAE 40
ABSTRACT
This study mainly focused on investigating the relationship between schooling and the earnings (wages) ofthe 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 ofschooling, 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 0.019 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 primary and 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. Govermuent 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.
GEOFREY, I (2022). Determinants of Schooling Returns; A Case Study of Employees of Atutur Hospital in Kumi District. Afribary. Retrieved from https://afribary.com/works/determinants-of-schooling-returns-a-case-study-of-employees-of-atutur-hospital-in-kumi-district-2
GEOFREY, ILAKUT "Determinants of Schooling Returns; A Case Study of Employees of Atutur Hospital in Kumi District" Afribary. Afribary, 28 Aug. 2022, https://afribary.com/works/determinants-of-schooling-returns-a-case-study-of-employees-of-atutur-hospital-in-kumi-district-2. Accessed 27 Dec. 2024.
GEOFREY, ILAKUT . "Determinants of Schooling Returns; A Case Study of Employees of Atutur Hospital in Kumi District". Afribary, Afribary, 28 Aug. 2022. Web. 27 Dec. 2024. < https://afribary.com/works/determinants-of-schooling-returns-a-case-study-of-employees-of-atutur-hospital-in-kumi-district-2 >.
GEOFREY, ILAKUT . "Determinants of Schooling Returns; A Case Study of Employees of Atutur Hospital in Kumi District" Afribary (2022). Accessed December 27, 2024. https://afribary.com/works/determinants-of-schooling-returns-a-case-study-of-employees-of-atutur-hospital-in-kumi-district-2