An Individual Level Test Of The Quot Feminization Of Poverty Quot Hypothesis Evidence From Ghana

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Copyright © 2014 SAGE Publications www.sagepublications.com
(Los Angeles, London, New Delhi, Singapore and Washington DC)
Vol 30(1): 25–43. DOI: 10.1177/0169796X13516351
An Individual Level Test of the
“Feminization of Poverty” Hypothesis
Evidence from Ghana
John Owusu-Afriyie
Department of Economics
University of Ghana
Legon, Accra
Edward Nketiah-Amponsah
Department of Economics
University of Ghana
Legon, Accra
ABSTRACT
Feminization of poverty is a hypothesis that postulates that women experience
poverty at higher rates than men. Over the years, empirical examination of
this hypothesis has relied on the comparison between poverty status of female-
headed and male-headed households due to lack of gender disaggregated data
in many household surveys. However, the use of poverty among female-headed
households as a representative measure of women’s poverty masks the extent of
poverty among women. Hence, this study uses individual gender disaggregated data
from the Ghana Living Standards Surveys IV and V (GLSS IV and V) and the
Foster–Greer–Thorbecke (FGT) classes of poverty measure to empirically test
the “feminization of poverty” hypothesis in Ghana. The study also finds out whether
this hypothesis is affected by the education level of the individual.
The article finds that “feminization of poverty” is prevalent at all three levels
of FGT poverty measures. The result further indicates that when education is
taken into consideration, “feminization of poverty” is found to be prevalent only
amongst the no education and primary education cohorts while masculinization
of poverty is rather found among the secondary and tertiary education cohorts.
Generally, in terms of the dynamic changes in “feminization of poverty,” the study
finds that over the last two sets of surveys (GLSS IV and V), the phenomenon has
reduced. Based on the results, we recommend that measures that target education
as a tool for combating poverty should be strengthened amongst females whilst
non-educational tools for combating poverty should target males.
Keywords: gender, poverty, inequality, education, FGT, Ghana

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26 Journal of Developing Societies 30, 1 (2014): 25–43
Introduction
The concept of “feminization of poverty” has gained currency over the
past few decades. Since the 1980s, studies on the proliferation of female-
headed households and research into gender-specific effects of structural
adjustment policies among others have led to increased attention to what
has become known as “the feminization of poverty” (Moghadam, 2005).
Pearce (1978) noted that poverty was becoming “feminized” in the United
States. According to Pearce, almost two-thirds of the poor over the age of
16 years were women (McLanahan & Kelly, 1999). This was what Pearce
referred to as “feminization of poverty,” a phenomenon where women
experience poverty at higher rates than men (Pearce, 1978). Adding to
his definition, Northrop (1990, p. 145) stated that “the feminization of
poverty is the process through which poverty become more concentrated
among individuals living in female-headed households.” Chant (2006)
also asserted that the key feature of the “feminization of poverty” is the
greater severity of women’s poverty relative to men.
However, over the years, due to lack of gender disaggregated data
at individual levels in many household surveys, most studies have laid
emphasis on the comparison between poverty status of female-headed
and male-headed households as a means of examining the evidence of
“feminization of poverty” (see BRIDGE, 2001; Buvinic & Gupta, 1994).
Consequently, analyses from household consumption and expenditure
surveys of many countries show a high incidence of poverty among female-
headed households (Fukuda-Parr, 1999). Particularly, in Ghana, Kyereme
and Thorbecke (1987) analyzed income data from the 1974/75 Household
Budget Survey and found that female-headed households accounted
for disproportionately higher levels of food poverty compared to male-
headed households. Similarly, Koster (2008) found that female-headed
households were poorer than male-headed households in post-genocide
Rwanda. Despite this pervasive conclusion, analyses from household
consumption and expenditure surveys of some countries have, however,
indicated a high incidence of poverty among male-headed households.
For instance, Ghana Statistical Service (GSS, 2007) indicated that since
the third round of the Living Standards Survey in Ghana, the incidence
of poverty among male-headed households has been greater than that of
their female-headed counterpart. Specifically, poverty incidence among
male-headed and female-headed households in 1991/92 were estimated as
55 percent and 43 percent respectively while in 1998/99 the figures were
41 percent and 35 percent respectively. In 2005/06, the poverty incidence

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Journal of Developing Societies 30, 1 (2014): 25–43
Owusu-Afriyie and Nketiah-Amponsah: “Feminization of Poverty” 27
among male-headed and female-headed households had reduced to
31 percent and 19 percent respectively. Thus, in Ghana, female-headed
households have over the years been better off than their male-headed
counterparts in terms of the rate of reduction in poverty. This is because,
according to Twerefou et al. (2013), most households with male heads
are found in the savannah and rural areas, which are prone to poverty.
Generally, the use of gender of the household head to examine the
evidence of “feminization of poverty” has resulted in mixed results.
In view of this, Fukuda-Parr (1999) argued specifically that the use of
poverty among female-headed households as a representative measure
of women’s poverty masks the extent of poverty among women. This
is because the measure is cast in a narrow framework of poverty that
focuses on the household as a unit, a focus that leads to ignoring intra-
household disparities (Fukuda-Parr, 1999). Moreover, according to
Women-in-Development (WID) and Gender and Development (GAD)
literature, intra-household inequalities is noted as one of the causes of
increased poverty among women (Moghadam, 2005) and thus should
be considered when analyzing women’s poverty. Empirical studies have
therefore raised conceptual and methodological doubt concerning the
relationship between female-headed households and poverty as well as
their use as a representative measure of women’s poverty. The conceptual
doubt is that female-headed households contain a highly varied universe,
“a universe that does not include all poor women and whose members are
not all poor’’ (Geldstein 1997, quoted in Feijoó, 1998). In addition, Chant
(2003) argued that poverty is rather a function of subjective elements.
Hence, it is imperative that “feminization of poverty” is viewed as an
individual-level phenomenon rather than a household-level phenomenon.
This means that “feminization of poverty” hypothesis should be examined
with respect to the gender of the individual household member rather
than the gender of the household head. Thus, using individuals aged
16 years old and above as the unit of analysis, this article tests empirically
whether “feminization of poverty” is prevalent in Ghana. The article
further investigates the effect of educational attainment of the individual
on the phenomenon.
Literature Review
Most empirical studies that examine the evidence of “feminization
of poverty” have used the gender of the household head as a unit of
analysis. For instance, in Botswana, Kossoudji and Mueller (1983) used

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Rural Income Distribution Survey conducted in 1974–1975 to analyze
the demographic and economic status of female-headed households in the
rural areas. Their findings indicated that female-headed households were
poorer than male-headed households and that on a per adult equivalent
basis, the welfare attained by members of female-headed households was
nearly 25 percent lower than that attained in male-headed households,
which may be regarded as an indication of “feminization of poverty.”
McLanahan (1985) also used longitudinal data taken from the Michigan
Panel Study of Income Dynamics to address the questions of whether
and why off-springs in female-headed households are more likely to
experience persistent poverty in adulthood. The findings showed that
growing up in a female-headed household increases the risk of poverty.
Similarly, Rodgers (1990) concluded that in the United States, male-
headed (single-parent) families are less poor than female-headed (single-
parent) families, which may be regarded as an indication of “feminization
of poverty.” In Tanzania, Katapa (2005) examined the characteristics of
female-headed and male-headed households, compared these households,
and related them to poverty. He concluded that female-headed house-
holds were more likely than male-headed households to be in rural areas,
be small in size, have fewer men, not have radios and not have enough
food to eat, which may also be regarded as an indication of “feminiza-
tion of poverty.”
In Ghana, Kyereme and Thorbecke (1987) analyzed income data
from the 1974/75 Household Budget Survey of Ghana and found that
female-headed households accounted for disproportionately higher levels
of food poverty compared to male-headed households, which may be
implied as “feminization of poverty.” Furthermore, Codjoe (2010) exam-
ined the population–food crop production nexus and within it assessed
the differences between male-headed and female-headed households.
He concluded that female-headed households in the transitional agro-
ecological zone produced more maize, owned more land, earned more
from the sale of maize, allowed more years for the land to fallow, used
more inorganic fertilizer on their farms, cropped more agricultural land,
and cropped maize on soils with better water absorption capacity, com-
pared to male-headed households, meaning female-headed households
are not worse off than male-headed households. Though the author did
not link the findings directly to poverty, it could be read as evidence
against “feminization of poverty.” Ofori (2011) using logistic regression
shows that male household heads are about 33.6 percent points likely

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to be less poor compared to their female counterparts. This therefore
supports the “feminization of poverty” phenomenon. However, a related
problem with the “feminization of poverty” is its over-concentration
on female-headed households (Chant, 2006). Strengthening the case
against the undue emphasis on female-headed households as a means of
measuring the phenomenon of “feminization of poverty,” Chant (2003)
argued that female-headed households are a highly heterogeneous
group (including both the poor and rich). In view of this problem,
Ofori (2011) focused on only the household head as a unit of analyzing
“feminization of poverty.” However, the problem of using the head of
the household as a unit of analysis is that not all females and males are
household heads. Hence, there is sample selection problem in his study.
Furthermore, some studies in Ghana have also analyzed poverty
without paying attention to its gender dimension. For instance, Adjasi
and Osei (2007) examined the nature and correlates of poverty in general.
Using the Foster–Greer–Thorbecke (FGT) poverty indicators and a
probit regression, the study found that a household is less likely to be
poor if the head is educated and urban based. They also conclude that
most households in Ghana rely on firewood, do not have access to pipe-
borne water and live in rooms rather than full apartments. However, the
underlying weakness of their study is that it is based on a static analysis of
poverty. Gyimah-Brempong and Asiedu (2009) investigated the effects of
international remittances on poverty incidence and severity at the house-
hold level using both cross-sectional data from Ghana Living Standards
Survey wave 5 (GLSS5) and pseudo-panel data constructed from
GLSS3-GLSS5 and a GMM pseudo-panel estimator. The study found
that international remittances decrease the probability of a family being
poor or chronically poor and increase human capital formation. Ennin
et al. (2011) modeled determinants of poverty using logistic regression
based on data from three rounds of the Ghana Living Standards Survey
(GLSS3, 1991/92; GLSS4, 1998/99; and GLSS5, 2005/06). The results
obtained from the analysis indicated that households with large sizes,
illiterate heads, and those with heads that have agriculture as their
primary occupation are poorer. Their study, however, did not focus on
the gender dimension of poverty.
The literature reviewed reveals that not many studies have been under-
taken to examine the “feminization of poverty” hypothesis in Ghana using
the individual household member as a unit of analysis. Moreover, pre-
vious studies have not adequately examined how education influences

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“feminization of poverty.” Thus, this study tests the hypothesis and con-
tributes to the empirical literature on the phenomenon.
Methodology
Theoretical Framework
Theoretically, this article employs the Individual Theory of poverty to test
the “feminization of poverty” hypothesis by Pearce (1978). The Individual
theory of poverty postulates that poverty is caused by the individual rather
than the community or household in which they live. Under this theory,
poverty is due to individual deficiencies and as such, anti-poverty pro-
grams in the light of this theory address poverty by focusing on individual
characteristics (Bradshaw, 2006). To subject the “feminization of poverty”
hypothesis to empirical test, this article employs the decomposable FGT
measure of poverty. This is because a useful feature of the FGT measure
is that it is additively decomposable with population share weights, specifi-
cally, with respect to male and female poverty (Wright, 1992). However,
most measures of poverty that incorporate Sen’s axiomatic requirements
(including Sen’s own measure) are not decomposable (see Hagenaars,
1987 and Wright, 1992). Therefore, for the purpose of this study, this is
problematic since we want to decompose the “total” amount of poverty
into male and female “shares.” Thus we employ the poverty measure of
Foster, Greer, and Thorbecke expressed as
(1)
Where I* is the income poverty line, Ii
is the income of individual i, q is
the number of poor individuals in the population (I* < Ii
), and n is the
total number of individuals in the population. a is a parameter that takes
on a value greater than or equal to zero (a ≥ 0).
As a gets larger, the measure becomes more sensitive to the income
circumstances of the “poorest poor” (Wright, 1992). If a = 0, then
P(0) = H =
q
n
. This is known as the head count ratio, which is the propor-
tion of the population that has income below the poverty line. If a = 1,
then P(l) = HI, where and I p is the average income of the
poor. This is a renormalization of the “income–gap ratio,” which captures

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the average income shortfall of the poor. This measures the poverty gap
and it captures the resources that would be needed to lift all the poor out
of poverty through perfectly targeted cash transfers (see Coulombe and
Wodon, 2007).
If a = 2, then
This is known as the squared poverty gap, which is a measure of the sever-
ity of poverty. This study limits itself to the first three measures of the
FGT class of poverty measures namely the head count ratio, the poverty
gap, and the squared poverty gap.
Following Wright (1992), we decompose the FGT class of poverty
measures into male and female poverty to examine the evidence of
“feminization of poverty” in Ghana. The decomposition is as follows:
, (2)
where the subscripts m and f denote male and female, respectively. The
ratios and are the population shares of males and females. p(a)f
and p(a)m
are the FGT poverty measures calculated separately for females
and males. According to Wright (1992), if p(a) is thought of as being the
total amount of poverty in the population, then the female and male
shares of this total are:
, (3)
(4)
From Equations (3) and (4), if the poverty experience is shared equally
between males and females, then S(a)f
= S(a)m
= 0.5. Hence, there is no
evidence of “feminization of poverty” at the individual level. Conversely,
if S(a)f
> p(a)m
, then poverty is not equally shared, with females

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being over-represented among the poor and we conclude that there is
“feminization of poverty” at the individual level.
Data
The data used in this article are from the fourth and fifth rounds of the
GLSS IV and V conducted in 1998/99 and 2005/06, respectively, by the
Ghana Statistical Service with the aid of the World Bank. The GLSS IV
and V are the two most recent surveys. The fourth round of the GLSS
covers 6,000 households in 300 enumeration areas whilst the fifth round
of the GLSS covers 8,687 households in 580 enumeration areas. Further,
the GLSS IV and V contain 30,000 and 37,128 individuals, respectively.
They also contain detailed information on a variety of topics, includ-
ing community level characteristics, the demographic characteristics of
households, education, health, employment, time use, migration, housing
conditions, agriculture, and non-farm businesses. Moreover, they contain
complete data on incomes of individuals, specifically men and women
which are essential for this study. Despite these advantages, they contain
a lot of missing data particularly on the education and income levels of
individuals. We therefore sampled 1,270 males and 1,576 females, aged 16
years old and above from the GLSS IV. From the GLSS V, we sampled
2,613 males and 3,021 females, who are aged 16 years and above. These
sample sizes are selected based on the availability of complete data on
individuals’ education and income levels in the two sets of survey. Table 1
therefore shows a breakdown of the sample data from the two sets of
survey used in our analysis.
Table 1.
Summary of Sampled Data from GLSS IV and V Used in the Analysis
GLSS IV GLSS V
Male Female Total Male Female Total
1,270 1,576 2,846 2,613 3,021 5,634
Identifying the Poor
Poverty is recognized to be multi-dimensional in its causes and manifesta-
tions, which includes lack of income and productive resources sufficient
to ensure a sustainable livelihood; hunger and malnutrition; ill health;
limited or lack of access to education and other basic services; increas-
ing morbidity and mortality from illness; homelessness and inadequate

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housing; unsafe environments; and social discrimination and lack of
participation in decision making (World Bank, 2000). This study employs
the income approach of measuring poverty as adopted by Wright (1992).
Specifically, the annual gross income of the individual (which is calculated
as a summation of individuals’ income from main and extra occupations,
and the value of goods received as income for work done) is used since
longer measurement period tends to help “smooth-out” short-term
fluctuations in income due to unemployment and overtime payments
(Wright,1992).Grossinsteadofnetincomeoftheindividualisusedbecause
the datasets (GLSS IV and V) do not contain actual amounts of deductions
such as Social Security Contributions, income taxes, and trade union dues.
Based on the datasets, an individual is classified as “poor” if his or
her annual gross income, Ii
, is below the poverty line, I*. According to
Hagenaars and Van Praag (1985), there are no well-defined rules for
selecting the appropriate poverty line. This article uses the so-called
“individuals below average income” (IBAI) approach, where the poverty
line is set at a fraction, β, of the mean level of income. That is: I*= β × I .
Therefore, an individual is poor if he or she earns an income below this
level. The implicit assumption underlying this approach is that the eco-
nomic resource of the individual is solely a function of his or her income.
In estimating the income poverty line, we set β to be equal to 48.6 percent
and 37.8 percent representing upper and lower poverty lines respectively.
This approach of poverty line definition is adapted from GSS (2007). Thus,
two income poverty lines are defined by this article. The upper income
poverty line is 48.6 percent of sample mean of income whilst the lower
income poverty line is set at 37.8 percent of sample mean of income. Our
objective of fixing two poverty lines is to find out whether our result is
robust to the choice of poverty line.
Results and Discussion
In this section, we present estimates of poverty indices separately for
males and females based on the three FGT poverty measures; the head
count poverty P(0), the poverty gap P(1), and the squared poverty gap
P(2) (see Tables 2, 3 and 4 respectively).
The Head Count Poverty Ratio – P(0)
This is a measure of the incidence of poverty. It is also known as the
poverty head count ratio. Table 2 shows the poverty head count ratio

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separately for males and females in 1998/99 and 2005/06 respectively.
We also carried out an analysis of this measure based on highest level
of education completed by individuals (males and females) in 1998/99
Table 3.
Male–Female Poverty Index: Index is P(1) ë 100
No
Education
Basic
Education
Secondary
Education
Tertiary
Education
All
Adults
Male Female Male Female Male Female Male Female Male Female
β = 0.486
1998/99 28.60 22.60 20.03 25.18 8.700 19.11 12.66 9.42 20.36 24.90
2005/06 28.73 37.79 32.40 34.90 35.97 29.27 30.77 27.03 36.53 42.63
β = 0.378
1998/99 22.72 17.76 14.71 19.34 40.81 14.64 6.53 6.75 15.31 19.10
2005/06 26.22 32.87 28.20 30.16 31.25 24.87 25.84 21.29 32.76 38.23
Source: Authors’ Computation from GLSS IV and V.
Table 2.
No
Education
Basic
Education
Secondary
Education
Tertiary
Education
All
Adults
β = 0.486
1998/99 53.85 45.83 44.43 50.00 32.17 32.35 43.84 21.21 43.78 48.73
2005/06 37.50 55.00 51.12 55.42 55.26 47.85 51.69 50.00 53.43 60.94
β = 0.378
1998/99 44.23 36.46 32.63 41.45 21.68 26.47 24.66 12.12 32.05 40.16
2005/06 37.50 55.00 43.90 47.20 49.21 39.71 44.92 45.65 46.08 54.35
Table 4.
No
Education
Primary
Education
Secondary
Education
Tertiary
Education
All
Adults
β = 0.486
1998/99 19.45 14.98 12.43 16.23 7.82 14.10 5.35 5.96 12.96 16.08
2005/06 22.02 28.58 25.70 27.50 28.06 21.89 22.70 19.44 30.51 35.34
β = 0.378
1998/99 15.29 11.50 9.16 12.17 163.74 12.12 2.60 4.60 9.73 12.09
2005/06 18.36 23.98 22.60 24.13 24.34 18.44 18.94 16.18 27.77 31.93

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and 2005/06 respectively. Using the head count poverty measure, the
all-adult sample indicates that females suffer poverty at higher rate than
males in the respective survey years regardless of educational level (see
Table 2). This means that if the effect of education is held constant,
females suffer poverty at higher rate than their male counterparts.
However, the tertiary-education cohort indicates that males suffer pov-
erty at higher rate than females (see Table 2). This means that females
having tertiary education as highest level of education completed suffer
poverty at a lesser rate than their male counterparts. Further, this could
imply that tertiary education is more effective in reducing poverty among
females than males. Thus education is an effective tool for combating
poverty among females. Table 2 further indicates that generally, the
head count poverty ratio for males and females has increased over the
respective years. Specifically, the all-adult head count poverty increased
by approximately 10 and 12 percentage points for males and females,
respectively. The results are robust to the choice of poverty line (β).
The Poverty Gap – P(1)
This poverty index measures the depth of poverty and it also captures the
resources that would be needed to lift all the poor out of poverty through
perfectly targeted cash transfers (Coulombe and Wodon, 2007). Table 3
shows the poverty gap rates calculated separately for males and females
in 1998/99 and 2005/06 respectively. Similarly, using the poverty gap
measure, the all-adult sample indicates that females have higher depth
of poverty than males in the respective years regardless of educational
level (see Table 3). This implies that when the effect of education is held
constant, females’ depth of poverty is higher than that of their male coun-
terparts. On the contrary, the secondary and tertiary education cohorts
indicate that females’ depth of poverty is lower than that of females with
the exception of 1998/99 (see Table 3). This is an indication that secondary
and tertiary education is more effective in reducing the depth of poverty
among females than males. These results are also robust to the choice
of poverty line (β).
The Squared Poverty Gap – P(2)
This index is a measure of severity of poverty and takes into account
the inequality among the poor (Coulombe and Wodon, 2007). Table 4
shows the poverty severity index of males and females in 1998/99 and

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2005/06 respectively. From Table 4, the all-adult cohort indicates that
when the effect of education is held constant, poverty is more severe
among females than males in the respective years. Conversely, the second-
ary and tertiary education samples indicate that poverty is more severe
among males than females (see Table 4). In other words, this could imply
that secondary and tertiary education is very effective in reducing the
severity of poverty among females than among males. These results are
also robust to the choice of poverty line (β).
From Tables 2, 3, and 4, all three measures of poverty; the head count
ratio, the poverty gap, and the squared poverty gap indicate that poverty
is higher among females than among males but with secondary or tertiary
education this trend reverses. Moreover, the three measures of poverty
calculated separately for males and females are robust to the choice of
poverty line (β).
Male–Female Poverty Shares Based on the FGT Poverty Measures – S(a)
This section provides the estimated male–female poverty shares based on
the three FGT classes of poverty measure. Based on the estimated poverty
shares, we conclude whether “feminization of poverty” is prevalent in
Ghana or not. Moreover, to test the statistical significance of the male–
female poverty share differences, we apply the paired samples T-test. We
alsoanalyzetheeffectofeducationonthemale-femalepovertyshares.This
is done to investigate the effectiveness of the various levels of education
in reducing poverty among males and females. Tables 5, 6, and 7 indicate
Table 5.
Male–Female Poverty Shares Based on P(0) – S(0) ë 100
No
Education
Basic
Education
Secondary
Education
Tertiary
Education
All
Adults
β = 0.486
1998/99 38.75 61.25** 48.05 51.95* 80.91 19.09*** 68.88 31.12*** 42.37 57.63***
2005/06 21.78 78.22** 47.98 52.02* 68.20 31.80*** 72.67 27.33*** 42.75 57.25***
β = 0.378
1998/99 39.51 60.49** 43.06 56.94* 77.74 22.26*** 81.91 18.09*** 39.50 60.50***
2005/06 21.78 78.22** 48.19 51.81* 69.71 30.29*** 71.67 28.33*** 41.94 58.06***
Notes: *** male–female poverty share difference is significant at 1%;** male–female poverty
share difference is significant at 5%;* male–female poverty share difference is significant
at 10%.

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the poverty shares of men and women based on the three FGT classes of
poverty measure – the head count ratio, the poverty gap, and the squared
poverty gap respectively.
Poverty Shares of Males and Females Based on P(0)
This relates to the shares of men and women in poverty based on the
head count ratio – P(0). From Table 5, when the effect of education
is held constant, women are found to be more represented among the
poor than men. Specifically, the shares of men and women in poverty
in 1998/99 are 42.37 percent and 57.63 percent respectively (see Table 5).
However, in 2005/06, the poverty shares of men increased to 42.75 percent
whilst that of women reduced to 57.25 percent (see Table 5). Moreover,
though the poverty share of women has been greater than that of men
in both years of the living standards survey, Table 5 indicates that the
gap in their poverty shares has reduced from 15.26 percent in 1998/99 to
14.50 percent in 2005/06. Therefore, this indicates “feminization of poverty”
but has not worsened over the years. However, when educational level
is considered, the share of men in poverty with secondary and tertiary
education is greater than that of women with secondary and tertiary
education. Specifically, when β = 0.486 (upper poverty line), the share
of men in poverty with secondary education is 80.91 percent in 1998/99,
which plummets to 68.20 percent in 2005/06, whereas the share of
women in poverty with secondary education is 19.09 percent in 1998/99,
which increases to 31.80 percent in 2005/06. This indicates that though
Table 6.
No
Education
Basic
Education
Secondary
Education
Tertiary
Education
All Adults
β = 0.486
1998/99 40.53 59.47** 45.29 54.71* 66.00 34.00* 74.95 25.05*** 40.08 59.92***
2005/06 23.07 76.93** 48.14 51.86* 69.53 30.47* 74.54 25.46*** 42.20 57.80***
β = 0.378
1998/99 40.79 59.21** 42.22 57.78* 109.19 –9.19* 68.29 31.71*** 39.61 60.39***
2005/06 24.57 75.43** 48.32 51.68* 70.00 30.00* 75.73 24.27*** 42.20 57.80***
at 10%.

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the share of women in poverty with secondary education has increased
over the respective years, there is no evidence for “feminization of
poverty” among this cohort but rather what Wright (1992) termed as
“masculinization of poverty.” Table 5 also indicates that in all the two
respective years (1998/99 and 2005/06), men with tertiary education have
a higher share of poverty than their women counterparts. For instance,
the shares of men with tertiary education in poverty are 68.88 percent
and 72.67 percent in 1998/99 and 2005/06 respectively whilst the shares
of women in poverty with tertiary education are 31.12 percent and
27.33 percent, respectively. This indicates that poverty share of men with
tertiary education has increased by 3.79 percent, whereas that of women
with tertiary education has reduced by the same percentage points. The
result also shows that there is no evidence for “feminization of poverty”
among the tertiary education cohort. Again, these results are robust to
the choice of poverty line (β).
Table 6 indicates the shares of men and women in poverty based on the
poverty gap index – P(1). We observe from our analysis that holding
educational effect constant, the percentage share of women who are in
poverty based on the second measure of poverty, P(1) is greater than that
of men. This indicates “feminization of poverty” at the P(1) level of pov-
erty measure. For instance, when the upper poverty line (i.e., β = 0.48) is
considered, regardless of the level of education, the shares of men in
poverty are estimated at 40.08 percent and 42.20 percent in 1998/99
and 2005/06 respectively whereas the shares of women in poverty are
estimated as 59.92 percent and 57.80 percent in 1998/99 and 2005/06,
respectively (see Table 6). Table 6 also indicates that the gap between
male and female poverty shares declines from 19.84 percent in 1998/99
to 15.60 percent in 2005/06. This indicates that though “feminization
of poverty” is found to be evident in 1998/99, it is found to be less pro-
nounced in 2005/06.
However, when educational level of the individual is factored into the
analysis, our results indicate that the share of men in poverty is greater
than that of women in poverty. For instance, when we consider the upper
poverty line (i.e., β = 0.48), the secondary education cohort indicates that
the shares of men in poverty based on P(1) are estimated as 66.00 percent
and 69.53 percent respectively in 1998/99 and 2005/06 whilst that of women
are estimated as 34.00 percent and 30.47 percent, respectively, in 1998/99

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and 2005/06 (see Table 6). For the tertiary education cohort, the shares
of men in poverty are estimated as 74.95 percent and 74.54 percent,
respectively, in 1998/99 and 2005/06 whilst those of women are estimated
as 25.05 percent and 25.46 percent, respectively, in 1998/99 and 2005/06
(see Table 6). Therefore, our results show that there is no evidence of
“feminization of poverty” among the secondary and tertiary education
cohorts based on this poverty measure. This result is also robust to the
choice of poverty line (β).
Table 7 shows the shares of men and women in poverty based on the
squared poverty gap – P(2). In other words, it shows the shares of men
and women in severe poverty. When the effect of education is isolated, the
share of women who suffer from severe poverty is higher than the share
of men who suffer from severe poverty (see Table 7). This according to
Chant (2006) is a feature of “feminization of poverty.” Similarly, Table 7
indicates that the shares of men in severe poverty are greater than those
of women in severe poverty. Specifically, under β = 0.486 (upper poverty
line), the estimated shares of men in severe poverty are 70.28 percent
and 70.42 percent respectively in 1998/99 and 2005/06 for the secondary
education cohort whilst women’s estimated shares of severe poverty
in 1998 and 2005/06 are 29.72 percent and 29.58 percent respectively.
For the tertiary education cohort, under β = 0.486, men’ shares of
severe poverty in 1998/99 and 2005/06 are estimated as 66.64 percent
Table 7.
No
Education
Primary
Education
Secondary
Education
Tertiary
Education
All
Adults
β = 0.486
1998/99 41.15 58.85** 44.36 55.64* 70.28 29.72** 66.64 33.36** 39.74 60.26***
2005/06 23.94 76.06** 48.31 51.69* 70.42 29.58** 75.02 24.98** 42.38 57.62***
β = 0.378
1998/99 41.72 58.28** 41.97 58.03* 98.29 1.71** 55.71 44.29** 39.70 60.30***
2005/06 23.82 76.18** 48.36 51.64* 71.03 28.97** 75.06 24.94** 42.56 57.44***
at 10%.

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and 75.02 percent, respectively, for the secondary education cohort whilst
women’s shares of severe poverty in 1998 and 2005/06 are estimated
as 33.36 and 24.98 percent respectively. Thus, at this level of poverty
measure, there is no evidence of “feminization of poverty” amongst the
secondary and tertiary education cohorts.
Based on the estimated male–female poverty shares in respect of
the three FGT poverty measures (as indicated in Tables 5, 6 and 7), it
is evident that generally there is “feminization of poverty” in Ghana.
However, when we examine the educational effect on this conclusion, our
estimates show that “feminization of poverty” is prevalent only amongst
the no education and primary education cohorts. However, amongst the
secondary and tertiary cohorts, what we rather find is what Wright (1992)
termed as “masculinization of poverty.” Generally, we also observe from
our estimated poverty shares in Tables 5, 6 and 7 that as the educational
level of males increases, their poverty share does not reduce. This means
that education is not a sufficient “weapon” for combating poverty amongst
males. However, as the educational levels of females increase, we observe
a reduction in poverty share. This means that education is rather a potent
“weapon” for combating poverty amongst females.
Policy Recommendation and Conclusion
In conclusion, our analysis of the two sets of household survey data (GLSS
IV and V) using the three FGT classes of poverty measures supports the
claim of “feminization of poverty” made by Pearce (1978). The first is that,
in general, all three classes of poverty measures indicate that women are
more represented in the ranks of the poor than men. This is contrary to
the findings of Wright (1992), which lends no support to the “feminiza-
tion of poverty” claim. Our analyses also indicate that over the last two
sets of household surveys (1998/99 and 2005/06), the head count poverty
ratio for males in general has increased significantly from 43.78 percent
to 53.43 percent whilst that of females has increased significantly from
48.73 percent to 60.94 percent (see Table 2). Similarly, the poverty
depth index for males in general has increased from 20.36 percent to
36.53 percent, whereas that of females has increased significantly from
24.90 percent to 42.63 percent (see Table 3). Furthermore, the poverty
severity index for males has increased from 12.96 percent to 30.51 per-
cent, whereas that of females has also increased significantly from 16.08
percent to 35.34 percent. Hence, over the two survey periods, all three
FGT indices of poverty have increased. Our results further indicate that

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though there is evidence of “feminization of poverty” in both years of the
survey, the trend reverses with high levels of education. Specifically, at
lower level of education (primary education) of the individual household
member, “feminization of poverty” is found to be prevalent but at higher
levels of education (secondary and tertiary), “masculinization of poverty”
is rather found to be prevalent. Therefore, further studies should be car-
ried out in order to investigate this. In terms of gender-specific policies
and strategies for combating poverty, we recommend that since females’
poverty shares reduce with increasing level of education, measures that
target education as a tool for combating poverty should be strengthened
amongst females whilst education in tandem with complementary inter-
ventions such as entrepreneurial training should be pursued in combating
poverty among males.
REFERENCES
Adjasi, C.K.D., & Osei, K.A. (2007). Poverty profile and correlates of poverty in
Ghana. International Journal of Social Economics, 34(7), 449–471.
Bradshaw, T.K. (2006). Theories of poverty and anti-poverty programs in
community development RPRC. Working Paper No. 06–05.
BRIDGE. (2001). Briefing paper on the feminisation of poverty. Institute of
Development Studies. Prepared by BRIDGE for the Swedish International
Development Cooperation Agency (SIDA).
Buvinic, M., & Gupta, R.G. (1994). Targeting poor woman-headed households
in developing countries: Views on a policy dilemma. Washington, DC:
International Center for Research on Women.
Chant, S. (2003). New contributions to the analysis of poverty: Methodological and
conceptual challenges to understanding poverty from a gender perspective, Serie
Mujer y desarrollo. No. 47 (LC/L.1955-P), Sales No. E.03.II.G.110, Santiago,
Chile, Economic Commission for Latin America and the Caribbean (ECLAC).
Chant S. (2006). Re-visiting the “feminisation of poverty” and the UNDP gender
indices: What case for a gendered poverty index?, New series working paper
18. LSE Gender Institute, London School of Economics and Political Science,
London, UK.
Codjoe, N.A.S. (2010). Population and food crop production in male- and female-
headed households in Ghana. Regional Institute for Population Studies,
University of Ghana, Accra, Ghana.
Coulombe, H., & Wodon, Q. (2007). Poverty, Livelihoods And Access to Basic
Services in Ghana. Discussed at the Ghana CEM technical review growth
workshop in Accra.

N
O
T
F
O
R
C
O
M
M
E
R
C
I
A
L
U
S
E
Ennin, C.C., Nyarko, P.K., Agyeman, A., Mettle, F.O., & Nortey, E.N.N. (2011).
Trend analysis of determinants of poverty in Ghana: Logit approach. Research
Journal of Mathematics and Statistics, 3(1), 20–27.
Feijoó, M.C. (1998). Dimensiones subjetivas de la pobreza. In Irma Arriagada
& Carmen Torres (Eds), Género y pobreza. Nuevas dimensiones, No. 26.
Santiago, Chile: ISIS International, Ediciones de las Mujeres.
Fukuda-Parr, S. (1999). What does feminization of poverty mean? It isn’t just
lack of income. Feminist Economics, 5(2), 99–103.
Geldstein, R.N. (1997). Mujeres jefas de hogar: familia, pobreza y género. Buenos
Aires: United Nations Children’s Fund (UNICEF).
Ghana Statistical Service. (2007). Pattern and trends of poverty in Ghana (1991–
2006). Accra, Ghana: Ghana Statistical Service.
Gyimah-Brempong, K., & Asiedu, E. (2009). Remittances and poverty in Ghana,
4th African Economic Conference (AEC), Department of Economics,
University of South Florida and Department of Economics, University of
Kansas.
Hagenaars, A. (1987). A class of poverty indices. International Economic Review,
28(3), 583–607.
Hagenaars, A.J.M., & Van Praag, B.M.S. (1985). A synthesis of poverty line
definitions. Review of Income and Wealth, 31(2), 139–154.
Katapa, R.S. (2005). A comparison of female- and male-headed households
in Tanzania and poverty implications. Journal of Biosocial Science, 38(3),
327–339.
Kossoudji, S., & Mueller, E. (1983). The economic and demographic status of
female-headed households in rural Botswana. Economic Development and
Cultural Change, 31(4), 831–859.
Koster, M. (2008). Linking poverty and household headship in post-genocide
Rwanda. Paper selected for presentation at the HiCN’s Fourth Annual
Workshop Yale University, New Haven, USA.
Kyereme, S., & Thorbecke, E. (1987). Food Poverty Profile and Decomposition
Applied to Ghana. World Development, 15(9), 1189–1199.
McLanahan, S. (1985). Family structure and the reproduction of poverty.
American Journal of Sociology, 90(4), 873–890.
McLanahan, Sara & Kelly, Erin. (1999). The feminization of poverty: Past
and future. In J. Chafetz (Ed.). Hand book of the Sociology of Gender
(pp. 127–145). New York: Plenum Publishing Corp.
Moghadam, V.M. (2005). The ‘feminization of poverty’ and women’s human
rights. SHS/HRS/GED SHS Papers in Women’s Studies/Gender Research,
UNESCO Working Paper No. 2.

N
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S
E
Northrop, E. (1990). The feminization of poverty: The demographic factor and the
composition of economic growth. Journal of Economic Issues, 24(1), 145–160.
Ofori, F. (2011). Free riding and the incidence of poverty in Ghana. Unpublished
M.Phil Thesis, Department of Economic, University of Ghana, Legon.
Pearce, D. (1978). The feminization of poverty: Women, work, and welfare.
Urban and Social Change Review, 11(1 & 2), 28–36.
Rodgers, R.J. (1990). Poverty and household Composition, Working Paper
No. 39, Department of Economics, University of North Carolina and The
Jerome Levy Economics Institute of Bard College.
Twerefou, D.K., Senadza, B., & Owusu-Afriyie, J. (2013). Determinants of poverty
among male-headed and female-headed households in Ghana, 18th Annual
African Econometric Society Conference Paper.
World Bank. (2000). World development report 2000–2001. Washington, DC:
World Bank.
Wright, R.E. (1992). A feminization of poverty in Great Britain? University of
Glasgow. Review of Income and Wealth Series, 38(1), 17–25.
John Owusu-Afriyie holds a Master of Philosophy degree in Economics
from the University of Ghana. His research interests are in the areas of
gender, poverty and inequality, capital markets, education, labor econom-
ics and climate change. He is currently a Principal Research Assistant
at the Department of Economics, University of Ghana and will soon be
pursing his PhD. [email: jon.owusuafriyie@gmail.com]
Edward Nketiah-Amponsah is a Senior Lecturer at the Department of
Economics, University of Ghana. He holds a PhD with Specialization
in Development and Health Economics from the University of Bonn,
Germany. His research interest includes the economics of healthcare
utilization, applied microeconometrics, social protection & poverty reduc-
tion, public expenditure and taxation analyses.
[email: enamponsah@ug.edu.gh/enamponsah@uni-bonn.de]

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