Health and life expectancy: testing for the validity of socio-economic disparity in the Philippines 6

By: Maricon R. Angco, Khylle Xavier G. Bautista, Lovely Danica S. Bituin, Maria Audrey D. Sison 4 0 16, [, ] | [, ] |
Contributor(s): 5 6 [] |
Language: Unknown language code Summary language: Unknown language code Original language: Unknown language code Series: ; 4453146Edition: Description: 27 pagesContent type: text Media type: unmediated Carrier type: volumeISBN: ISSN: 2Other title: 6 []Uniform titles: | | Related works: 1 40 6 []Subject(s): -- 2 -- 0 -- -- | -- 2 -- 0 -- 6 -- | 2 0 -- | -- -- 20 -- | | -- -- -- -- 20 -- | -- -- -- 20 -- --Genre/Form: -- 2 -- Additional physical formats: DDC classification: | LOC classification: | | 2Other classification:
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Action note: In: Summary: Abstract One of the most important population health and economic development indices is life expectancy. The World Bank (1993) found that the lower the per capita GNI, the lower the life expectancy. William and Boehmer (1997) show that one's educational status has a positive and significant impact on life expectancy. This study aims to analyze the correlation between life expectancy and income. To do so, the researchers collected time-series data from 1990 to 2019 from the World Bank Open Data. The disturbance term and level of significance used in hypothesis testing are 0.05. The dependent variable used was life expectancy, while GNI per capita growth (annual %) was the primary explanatory variable. The proponents of this study also included several additional explanatory variables which are employment to population ratio, 15+, total (%) and school enrollment, secondary (% gross). The results revealed a positive link between life expectancy and GNI per capita growth. Higher-income and education increase the health production benefit, and education increases the efficiency of health investment. Furthermore, the results prove the employment has a negative effect on life expectancy. Those who engage in labor-intensive jobs have poorer health than those who work in professional occupations Keywords: life expectancy, income, GNI per capita, employment, education Other editions:
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Business Research: (BSBA major in Business Economics) - Pamantasan ng Lungsod ng Maynila, 2021 56

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Abstract One of the most important population health and economic development indices is life expectancy. The World Bank (1993) found that the lower the per capita GNI, the lower the life expectancy. William and Boehmer (1997) show that one's educational status has a positive and significant impact on life expectancy. This study aims to analyze the correlation between life expectancy and income. To do so, the researchers collected time-series data from 1990 to 2019 from the World Bank Open Data. The disturbance term and level of significance used in hypothesis testing are 0.05. The dependent variable used was life expectancy, while GNI per capita growth (annual %) was the primary explanatory variable. The proponents of this study also included several additional explanatory variables which are employment to population ratio, 15+, total (%) and school enrollment, secondary (% gross). The results revealed a positive link between life expectancy and GNI per capita growth. Higher-income and education increase the health production benefit, and education increases the efficiency of health investment. Furthermore, the results prove the employment has a negative effect on life expectancy. Those who engage in labor-intensive jobs have poorer health than those who work in professional occupations Keywords: life expectancy, income, GNI per capita, employment, education

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