Poverty and Human Resources
Poverty and Human Resources
children. The poor may not be able to spare their children - particularly their girls - from household work
in order to go to school. A study of gender differences in performance in the primary-leaving examination
in the Cote d’Ivoire found that the difference arose due to the under-performance of girls from poor
households. This may reflect the demands on the time of girls in poor households. In their last two
years of primary school, girls from the poorest 25% of households reported spending 16 hours a week
in school and 15 hours on housework; in the most affluent 25% of households, the figures were 27
hours and 7 hours respectively (Appleton, 1995a). Poor households may also not be able to afford the
monetary costs of health care and education. These costs may help explain why the benefits of postprimary
schooling accrue mainly to the non-poor. A beneficiary assessment of social sector spending
in Tanzania found the poorest and most affluent quintiles received 19% and 18% respectively of
expenditure on primary schooling; but for secondary schooling, the poorest received only 8% and the
most affluent received 36%. All university expenditure was estimated to accrue to the richest 20% of
the population (World Bank, 1995). However, non-monetary factors are also important: lack of parental
education is often found to be more critical than a lack of income per se in determining child health,
performance at school and eligibility for post-primary education.
Household surveys provide useful evidence on the distribution of investments in human capital. For
example, survey data for Cote d’Ivoire in 1985 showed net primary school enrolment rates for boys to
be 32% amongst the poorest 10% of the population but 66% amongst the non-poor (defined as the top
70% of the population. For girls, the corresponding figures were 22% and 54%. Interestingly, girls from
poor households appear to have suffered more from the country’s economic decline in the 1980s: by
1988, net primary school enrolments for girls in very poor households had declined to 17% whilst
amongst the non-poor they had risen to 57%. Male primary school enrolments rose in non-poor
households and remained constant in very poor ones. Poverty was also strongly correlated with use of
curative and preventive health care, although here gender differences were less marked. In 1985, 31%
of very poor males consulted a doctor or nurse when sick; amongst the non-poor the figure was 51%
(Grootaert, 1994). By 1988, the inequalities had widened, with the corresponding proportions being
19% and 53%.
Poverty profiles of African countries invariably find rates of poverty decline sharply with the education
of the household head. For example, in Nigeria in 1992, 39.5% of people in households with uneducated
heads were poor; for those living in households with secondary school educated heads, the poverty
rate was only 23% (World Bank, 1996). Education reduces poverty partly by giving access to high
return formal sector employment and to higher wages within such employment. However, there is
evidence that education and nutrition also raise productivity in farm and non-farm self-employment,
activities in which the poor are concentrated.
Human Capital and Economic Development
Simon Appleton and Francis Teal
Poverty and Human Resources - To learn more about this author, visit African Development Bank's Website.
Like this article? Share it with your friends
Poverty can prevent households from making high return investments in the human capital of their
children. The poor may not be able to spare their children - particularly their girls - from household work
in order to go to school. A study of gender differences in performance in the primary-leaving examination
in the Cote d’Ivoire found that the difference arose due to the under-performance of girls from poor
households. This may reflect the demands on the time of girls in poor households. In their last two
years of primary school, girls from the poorest 25% of households reported spending 16 hours a week
in school and 15 hours on housework; in the most affluent 25% of households, the figures were 27
hours and 7 hours respectively (Appleton, 1995a). Poor households may also not be able to afford the
monetary costs of health care and education. These costs may help explain why the benefits of postprimary
schooling accrue mainly to the non-poor. A beneficiary assessment of social sector spending
in Tanzania found the poorest and most affluent quintiles received 19% and 18% respectively of
expenditure on primary schooling; but for secondary schooling, the poorest received only 8% and the
most affluent received 36%. All university expenditure was estimated to accrue to the richest 20% of
the population (World Bank, 1995). However, non-monetary factors are also important: lack of parental
education is often found to be more critical than a lack of income per se in determining child health,
performance at school and eligibility for post-primary education.
Household surveys provide useful evidence on the distribution of investments in human capital. For
example, survey data for Cote d’Ivoire in 1985 showed net primary school enrolment rates for boys to
be 32% amongst the poorest 10% of the population but 66% amongst the non-poor (defined as the top
70% of the population. For girls, the corresponding figures were 22% and 54%. Interestingly, girls from
poor households appear to have suffered more from the country’s economic decline in the 1980s: by
1988, net primary school enrolments for girls in very poor households had declined to 17% whilst
amongst the non-poor they had risen to 57%. Male primary school enrolments rose in non-poor
households and remained constant in very poor ones. Poverty was also strongly correlated with use of
curative and preventive health care, although here gender differences were less marked. In 1985, 31%
of very poor males consulted a doctor or nurse when sick; amongst the non-poor the figure was 51%
(Grootaert, 1994). By 1988, the inequalities had widened, with the corresponding proportions being
19% and 53%.
Poverty profiles of African countries invariably find rates of poverty decline sharply with the education
of the household head. For example, in Nigeria in 1992, 39.5% of people in households with uneducated
heads were poor; for those living in households with secondary school educated heads, the poverty
rate was only 23% (World Bank, 1996). Education reduces poverty partly by giving access to high
return formal sector employment and to higher wages within such employment. However, there is
evidence that education and nutrition also raise productivity in farm and non-farm self-employment,
activities in which the poor are concentrated.
Human Capital and Economic Development
Simon Appleton and Francis Teal
Poverty and Human Resources - To learn more about this author, visit African Development Bank's Website.
Like this article? Share it with your friends
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