Female poverty in the Northern States of Malaysia

The male population in Malaysia is higher compared to female, but there are more female in education in comparison with male. According to the Statistics of Higher Education of Malaysia Report 2010, more than 60 per cent of enrolments in Public Higher Education Institutions are female. Even thoug...

全面介紹

Saved in:
書目詳細資料
Main Authors: Mohamad Azhar, Nur Azirah Zahida, Mohd, Saidatulakmal, Bahari, Zakaria
格式: Conference or Workshop Item
語言:English
出版: 2015
主題:
在線閱讀:http://eprints.usm.my/35092/1/PPIK17.pdf
http://eprints.usm.my/35092/
標簽: 添加標簽
沒有標簽, 成為第一個標記此記錄!
實物特徵
總結:The male population in Malaysia is higher compared to female, but there are more female in education in comparison with male. According to the Statistics of Higher Education of Malaysia Report 2010, more than 60 per cent of enrolments in Public Higher Education Institutions are female. Even though there are more female in tertiary education, but the wages for female employee are still lower compared to male employee. Somehow, this situation has contributed to female poverty. Among others, the factors known to influence female poverty are low education attainment, poor health, lack of gainful employment due to child rearing responsibility, involvement in low productivity jobs, divorce. While Malaysia has demonstrated successful reduction of poverty from more than 50 per cent in the 1970s to 0.6 per cent in 2014, there is no information on how female poverty has been affected over the years. The main objective of this study is to assess female poverty incidence in the Northern States of Malaysia. Specifically, the study aims to empirically determine the poverty incidences among female and the factors influencing the female poverty in the Northern States of Malaysia. The study found that 0.17 per cent of female in the Northern States are living in state of poverty. Female with lower education have higher incidence of poverty where 36 per cent and 21 per cent of them who have non-formal and primary education respectively are poor. Logistic probability function taking the value of 1 (female living in poverty) and 0 (female not living in poverty) is employed to determine factors influencing female poverty. The independent variables included are per capita income, income inequality by states and education attainment. All variables are found to be statistically significant in influencing female poverty.