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EMPIRICAL ANALYSIS OF CORRELATES OF EDUCATION IN THE SLUM POPULATION: AN EVIDENCE FROM KARACHI, PAKISTAN |
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| รหัสดีโอไอ | |
| Creator | Riaz Ahmed and Atta Ullah Khan |
| Title | EMPIRICAL ANALYSIS OF CORRELATES OF EDUCATION IN THE SLUM POPULATION: AN EVIDENCE FROM KARACHI, PAKISTAN |
| Contributor | - |
| Publisher | TuEngr Group |
| Publication Year | 2563 |
| Journal Title | International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies |
| Journal Vol. | 11 |
| Journal No. | 11 |
| Page no. | 11A11E: 1-9 |
| Keyword | Slum population, Logistic regression, Low school enrollment rate, Slum unemployment rate, Slum childs' education, Slum family head's income, Poverty study, Literacy rate, Slum study. |
| URL Website | http://TuEngr.com/Vol11_11.html |
| Website title | ITJEMAST V11(11) 2020 @ TuEngr.com |
| ISSN | 2228-9860 |
| Abstract | This paper empirically analyzes the correlates of education in the context of slums' population of Karachi, Pakistan. Primary data has been used in the study which was collected through a questionnaire. Through a stratified sampling technique, 380 households were selected from 20 sampled slums. The descriptive analysis includes literacy rate, education level of the unemployed population, percentage of school-aged children who are not attending school, and reasons for not attending the school are presented. A logistic regression model is used to explore the impact of important variables like per capita income of the family, education of family head, dependency ratio, access to school and educational expenses on the educational attainment of family. The literacy rate was found 37 percent while 51 percent of the school-aged children are not attending school. The major reason for children not attending the school is found to be poverty. It is also found that the majority of unemployment is due to illiteracy. The result of the regression model shows that per capita income and education of family head affect the educational attainment positively while dependency ratio, access to school, and expenses on education affect it negatively. |
