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Workneh Girma et al/ Assessment of Multidimensional Child Poverty in Ethiopia: The case of Dambi Dollo town, Oromia Regional State
Assessment of Multidimensional Child Poverty
in Ethiopia: The case of Dambi Dollo town,
Oromia Regional State
Workneh Girma1, Namo Gabisa2, Mulugeta Tesfaye3, Aboma Benti4
Dambi Dollo University, College of Business and Economics, Department of Economics, Ethiopia.
2
Dambi Dollo University, College of Business and Economics, Department of Economics, Ethiopia.
3
Dambi Dollo University, College of Business and Economics, Department of Management, Ethiopia.
4
Dambi Dollo University, College of Business and Economics, Department of Business management
and Entrepreneurship, Ethiopia.
Corresponding author’s Email:gabisanamo@gmail.com
1
ABSTRACT
Multidimensional child poverty is a deprivation experienced by children. To the level of the
authors no study has undertaken using primary data as well as at the study area and studies on the
assessments of multidimensional child poverty in Ethiopia is very limited. Available literatures have
focused on the comparison of urban and rural child poverty and have used traditional or one-dimension
approach which leads to a partial understanding of child poverty and ineffective policies of poverty
reduction. The purpose of this study was to assessmultidimensional child poverty inDambiDollo town
using the AF approach of 2011 with primary data sources and child as unit of analysis. The finding of the
study revealed that a school aged child of Dambi Dollo town was being deprived in housing, health,
information, care, sanitation, and education dimensions respectively with the incidence of poverty (H0 =
0.87) and the intensity (A=0.58 ) and the multidimensional child poverty adjusted head count ratio(M0)
is 0.502 at the poverty cut-off, k=2. Based on this, provision of aid programs and support, improving
access to education and health for all as the short run and directing economic resources to affected
children and their families, implementation of anti-natal policy, reduction of early age marriage,
promotion of gender equity, and mainstreaming child-targeted programs in to macroeconomic and
socialsectors development policies are the long run major forwarded recommendations.
Key words: School aged-Child, Multidimensional child poverty, Dimensions, Indicators, AF approach.
DOI Number: 10.14704/NQ.2022.20.16.NQ880102
NeuroQuantology2022;20(16):1016-1032
1. Introduction
While a severe lack of goods and
services hurts every human being, it is most
threatening and harmful to children. Leaving
them unable to enjoy their rights, reach their
full potential and to participate as full members
of society is the worst and continues
intergenerational poverty cycle. It was far that
the United Nations recognized child poverty as
children deprived of nutrition, water and
sanitation facilities, access to basic health-care
services, shelter, education, participation and
protection. According to this definition child
poverty is characterized by severe deprivation
of basic human needs which depends not only
on income but also on access to social service
(UNGA, 2006, pp 460).
Moreover, growing up in poverty can be
damaging to children’s physical, emotional and
spiritual development. Child poverty differs
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Workneh Girma et al/ Assessment of Multidimensional Child Poverty in Ethiopia: The case of Dambi Dollo town, Oromia Regional State
from adult poverty in that it has different
causes and effects, and the impact of poverty
during childhood can have detrimental effects
on children which are irreversible. It can cause
lifelong cognitive and physical impairment,
where
children
become
permanently
disadvantaged and this in turn perpetuates the
cycle of poverty across generations (UNICEF,
2011).
For this reason, states that ratify the
convention on the rights of the child (CRC) had
agreed that children have the right to survival,
development, protection and participation and
they agreed that they will do all they can
progressively to realize those rights.
Accordingly, the Ethiopian state had ratified the
CRC in 1991(MOFED and USAID, 2013). In
addition, the revised family code proclamation
no.213/2000 purports to give ‘priority to the
well-being, upbringing and protection of
children in accordance with the constitution
and international Conventions which Ethiopia
has ratified’ (MOLSA 2006: p71). According to
article 215 of the revised family code, a minor is
a person of either sex who has not attained the
full age of eighteen years’. The law presumes
that the minor is incapable of performing a
broad range of legally binding acts and in such
circumstances places him or her under the care
and protection of specified organizations (ibid:
p71-72).
However, the accomplishment of
Ethiopia in reduction of income poverty has not
been accompanied by improvements in other
important areas. In 2011, 87% of
Ethiopianpopulation wasmultidimensional poor
as measured by MPI which means as
multidimensional poverty index (MPI) they
were deprived in at least one third of the
weighted MPI indicators. This put Ethiopia as
the second poorest country in the world(OPHDI,
2014).With the recession of global economy
supported by financial crisis followed by covid19 pandemic crisis, Ethiopian economy has also
shared downturn of the economy aggravated by
the political unrest and foreign currency
drainage currently.
Manytown dwellers remain effectively cut off
from the benefits of citizenship. Because land
ownership or renting formal housing are out of
reach for so many households, they often live in
unauthorized informal settlements, under
bridges, along railway lines, on whatever land
that is not already occupied, even though it may
be hazardous or unfit for habitation. Children
living with those households fail in jobs beyond
their capacity and enforced to beg money and
remnants of food from restaurants and minicafés (Bartlett, 2011). Unplanned town
construction in the name of investment also
displaces households with their large family size
without considering children in the calculation
of compensation if applied. Moreover, any
children in the country reported in the extreme
need of basic necessities related health,
standard of living, and lack of access to
education (UNICEF, 2015). Hence, poverty is not
just about the capacity to afford a basic food
basket; it is a matter of lack of access and
exclusion in a range of areas.
This implies that poverty can be seen as
multidimensional contrary to the traditional
approach of income or consumption poverty
which is one-dimensional in any area.i.e. either
it isDambi Dollo town. The difference between
them is that the newly developed poverty
analysis has direct relationship with the unit
analysis whereas the monetary approach has
indirect relationship with the probability of
being
poor
or
not
(Alkire,
2015).Multidimensional child poverty measures
provide a more direct description of povertyas
experienced by children themselves and the
social and family environment in which they
live. They are also crucial to target policies and
programs towards the most deprived and
disadvantaged children in countries to ensure
they can be reached in the new sustainable
development goals (SDGS) by 2030 (UNICEF,
2014).
Moreover, looking at real income levels
or even the levels of consumption of specific
commodities cannot suffice as a measure of
well-being(Todaro, 2012), the monetary poverty
approach is inappropriate for estimating child
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Workneh Girma et al/ Assessment of Multidimensional Child Poverty in Ethiopia: The case of Dambi Dollo town, Oromia Regional State
poverty since so little is known about the
income or consumption needs of children and
how these may vary by age, gender and
location. For instance, children have low food
requirements but higher requirements in other
basic needs that require expenditure; whether a
child lives in poverty does not only depend on
family income but also on access to public
goods and services such as a safe water supply,
health care and education.
To pursue inclusive equity and
guarantee that benefits are distributed among
the population, it is crucial the country ensures
that the gains achieved by high levels of
economic growth trickle down to the most
vulnerable segments of the society. Even more
so in light of the negative health related and
socio-economic impacts caused by COVID-19
which have affected both monetary and
multidimensional child poverty levels (UNICEF,
Faces of Child poverty in Ethiopia,
2021)Povertyin childhood is more severe than
any of it as it passes to adulthood and becomes
intergenerational child poverty in the country.
In addition to becoming the most vulnerable
groups of a society, children are dependent on
their families. It also affects the mental,
psychology, spirit and motivation of them at the
stage which harms their future life. Moreover,
children are the more deprived to poverty than
any class of society (Alkire.et al, 2011).
Growing up in poverty can have a significant
detrimental impact on children’s quality of life
and well-being and has limiting effects on a
child’s opportunities and future life chances.
Poverty can have an impact on every area of a
child’s life, from health and well-being, to
education and employment. immediate
experiences in childhood children’s experiences
of poverty in childhood can have concerning
consequences on their mental health,
engagement with their education and their
family life etc. children living in poverty are also
frequently denied their rights: to survival,
health and nutrition, education, and protection
from harm, abuse and exploitation(UNICEF and
REPOA, 2009).
Poverty in childhood can cause lifelong
cognitive and physical impairment, where
children become permanently disadvantaged
and this in turn perpetuates the cycle of poverty
across generation (Engilbertsdotti, 2011).
Children who experience poverty during their
preschool and early school years have lower
rates of school completion than children and
adolescents who experience poverty only in
later years (Duncan, 1997). Moreover, children
living in poverty are more likely to become
impoverished adults and have poor children,
creating and sustaining intergenerational cycles
of poverty. While the largest costs of child
poverty are borne directly by children
themselves, society also pays a high price
through reduced productivity, untapped
potential and the costs of responding to chronic
poverty. Child poverty damages children’s life
chances and harms all society (UNICEF, 2014).
In order to give policy incentives and
work towards not only reducing the number of
poor children, but also reducing the intensity of
deprivations from which they suffer, identifying
key determinants, indicators and dimensions is
unquestionable (Plavgo, et al., 2013). Thus,
incorporation of child poverty into the
economic policy analysis is then crucial, in order
to have a deeper understanding of the
country’s situation and ensure the effectiveness
of social security and child protection policies
implemented (UNICEF, 2015).
Studies focused on multidimensional
child poverty in Ethiopia are rare in general and
no like researches have been done on the study
area so far, to the knowledge of the
researchers, in particular. Freweini (2013) on
the dynamics of child poverty and its
determinants in Tigray region has focused on
the determinants of nutritional child poverty on
under six years and its dynamism or change in
child poverty reduction over time using the
longitudinal data obtained from the young live
using young live approach. However, the study
focused on single component of indicator of
multidimensional child poverty i.e., nutritional
status. It used consumption/income poverty
approach .i.e. monetary approach to identify
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Workneh Girma et al/ Assessment of Multidimensional Child Poverty in Ethiopia: The case of Dambi Dollo town, Oromia Regional State
determinants of child poverty in Tigray region
(Freweini, 2013).
These studies, mentioned above, were
conducted on the nutritional status of children
under five but didn’t touch other dimensions of
poverty and the school aged children.Their
focus was on single deprivation and onedimensional
analysis.
However,
onedimensional analysis lead to a partial
understanding of poverty, and often to
unfocused or ineffective poverty-reduction
programs and policies that fail to capture many
aspects of deprivation and their interactions.
Thus, child poverty is multidimensional and
should be measured using multidimensional
approaches. It is a multidimensional including
health, education, and living standard as stated
in SDG to be reached by 2030 (UNICEF, 2015).
In addition, more available literatures on
the child poverty in Ethiopia are monetary
approach and their focuses were on the
measurement and patterns of deprivation on
the comparison between urban and rural. This
study fills the above gaps by using multiple
dimensions of indicators. Therefore, the main
objective of this study is to assess
multidimensional child poverty in Dambi Dollo
town and the specific objectives are:
 Analyzingthe severity of multidimensional
poverty among children living in study area
 Evaluating
the
socio-economic
characteristics of children in study area
 Classifying indicator/s in which children in
Dambi Dollo are deprived off.
2. Materials and Method
2.1. Data Source and Sampling Technique
This study is conducted in Dambi Dollo town,
the capital of Kelem Wollega zone, Oromia
National Regional State of Ethiopia. The town is
located at 652 km west of Finfine, the capital
city of Ethiopia. It is bounded by SayoWoreda in
all direction. In the study area there are 4
kebele administrations including Biftu, Dollo.
Lafto and Yabalo. The target population of the
studycovers the town’s households with a child
in the age of range 7-15 years old being lived
only. According to the office of Women and
Youth Affairs (2021), there are 2500 school
aged children in the town as of June of 2021.
The sample size was determined using stratified
random sampling technique from four kebele
(Dollo, Lafto, Biftu and Yabalo) kebeles of the
town. The total population of Dambi Dollo town
is 26,748. Out of which 1500 of them are school
aged children, children whose age are reached
for
school.
BasedonKothari(2004),thesamplesizewascalcula
tedusingthefollowingformula.
𝑛=
𝑧 2 pqN
2
𝑒 2(𝑁−1)+𝑧 pq
=288
Where, n: is thesamplesizeofafinitepopulation,
N:totalnumber of school aged children
p: population variability, where p is assumed
0.5 taken for unknown variability and p + q= 1,
e:margin oferror or levelof precision ,5%is
consideredforthis study, Z=Confidencelevel,
with 95%confidencelevel(0.05/2), z=1.96
The researchers have collected data from 288
school aged children and their families. Thus,
using Proportional sampling technique, 74
children are from Dollo, 67 are from Biftu, 80
are from Yaballo and 67 are from Lafto.Primary
data is collected from the respondents through
questionnaires. In addition, interview with
family and focus group discussion is held with
key informants from cross-cutting sector
leaders in the town.
2.2. Method of Data Analysis
2.2.1. Measuring Poverty
To identify indicators in which a given child is
deprived of, the intensity of the poverty and
percentage of children deprived in Dambi Dollo
town, the multidimensional poverty index
approach of Alkire and Foster (2011a) (AF)is
used.The Alkire-Foster approach includes two
steps: an identification method (ρk) that
identifies ‘who is poor’ by considering the range
of deprivations they suffer, and an aggregation
method that generates an intuitive set of
poverty measures (Mα) (based on traditional
FGT measures) that can be broken down to
target the poorest people and the dimensions
in which they are most deprived (Alkire, 2009).
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Workneh Girma et al/ Assessment of Multidimensional Child Poverty in Ethiopia: The case of Dambi Dollo town, Oromia Regional State
The AF method also proposes two additional
measures in the same class of multidimensional
poverty measures: the adjusted poverty gap
and the adjusted FGT measure, which are
sensitive to the depth of deprivation in each
dimension, and the inequality among the poor.
Thus, to fulfill the SDG goal of ‘leaving no one
behind’ it is necessary to be able to define who
the poorest of the poor are, and how their
situation is changing (Alkire, 2016).
As a measure, the MPI has the mathematical
structure of one member of a family of
multidimensional poverty measures proposed
by Alkire and Foster (2011a). This member of
that family is called Mo or adjusted headcount
ratio. It can be calculated for different groups in
the population, holds for monotonicity,
decomposable in to dimensions to reveal policy
makers what dimensions contribute the most to
multidimensional poverty in any given unit of
analysis.i.e. child in this case. Thus, it is the
appropriate measure to be used whenever one
or more of the dimensions to be considered are
of ordinal nature, meaning that their values
have no cardinal meaning”(Alkire.S and Santos,
M. E, 2014).
The MPIuses the multidimensional deprivation
headcount (H), representing the children whose
total number of deprivations is equal to or
above a specified cut-off, as a percentage of the
respective child population. Although it is a
good indication of deprivation incidence, the
head count ratio is not sensitive to the breadth
of multidimensional poverty, as it remains
unchanged regardless of whether children who
are identified as multidimensionality poor suffer
from deprivation increases simultaneously. For
this reason, two additional ratios will be used in
this analysis. The average deprivation intensity
among the deprived (A) measures the breadth
of multidimensional deprivation. It is calculated
using the number of deprivations that the
multidimensionality deprived children counted
encounter, divided by the maximum number of
deprivations the deprived children experience
(Alkire, et al., 2015).
The adjusted multidimensional deprivation
head count (Mo), adjusts the deprivation
headcount rate by the intensity of deprivation
and is calculated by the following formula:
∑𝑘 𝑞𝑘 𝑐𝑘
𝑀𝑜 = 𝑖 𝑛∗𝑑 Withck = Di*yk,
Where k = cut-off point (number of dimensions
a child should be deprived in to be
Considered as multidimensional poor
qk = number of children affected by at least k
deprivations
ck = number of deprivations each
multidimensional deprived child i experience
n = total number of children
d = total number of dimensions
considered per child
Di = number of deprivations each child i
experience
yk = deprivation status of a child i depending on
the cut-off point k with yk = 1 if Di >=k
yk = 0 if Di < k
Furthermore, the MPI reflects both the
incidence and headcount ratio (𝐻) of poverty –
the proportion of the population that is
multidimensional poor – and the average
intensity (𝐴) of their poverty – the average
proportion of indicators in which poor people
are deprived. It is calculated by multiplying the
incidence of poverty by the average intensity
across the poor (𝐻 × 𝐴). The MPI is the M0
measure with a particular selection of
dimensions, indicators and weights (Alkire,
Jindra, Robles, & Vaz, 2016).
Generally, steps to a multidimensional poverty
measure for ordinal data includes choosing unit
of analysis, choosing dimensions, choosing
indicators, setting cutoff, applying cutoff,
counting the number of deprivation for each
individual, setting the second cutoff, applying
cutoff “k” to obtain the set of poor children and
censor all non-poor data, calculating the head
count “h”, calculating the average poverty gap
“A”, calculating the adjusted head count “MO”,
and finally decomposing by group and breaking
down by dimension. These steps will be
followed in this study (Alkire, 2009).
2.2.2. Modeling Multidimensional Poverty
Index
Let y= [yij] denote the n x d matrix of
achievements, where n represents the number
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of children, d is the number of dimensions, and
yij ≥ 0 is the achievement of child i= 1, 2…..,nin
dimension j=1,2,…d. each row vector yi= yi1, y
i2,……, yid lists child i’s achievements, while each
column vector y0j = y1j,y2j,….ynj gives the
distribution of dimension j achievements across
the set of children. Let zj> 0 denotes the cutoff
below which a child is considered to be
deprived in dimension j and let z be the row
vector of dimension specific cutoff (Alkire,
"Multidimensional Poverty Measurement and
Analysis", 2015).
The expression |v| denotes the sum of all the
elements of any vector or matrix v, and µ(v)
represents the mean of |v|, or |v| divided by
the total number of elements in v. for a given
matrix of achievements y, it is possible to define
a matrix of deprivation g0=[g ij0 ] whose typical
element gij0 is defined by g ij 0 =1 when yi<zj,
while gij 0 = 0 otherwise. Hence, g0 is an n x d
matrix whose ijth entry is 1 when child I is
deprived in dimension j, and 0 otherwise
according to each dimension cutoff zj. From this
matrix, we can construct a column vector c of
deprivation counts, whose ith entry ci= |g0 i |
represents the number of deprivations suffered
by child. Notice that the matrix and vector can
be defined for any ordinal and cardinal variable
from the matrix of achievements y.
Following Alkire and Foster (2011a), the vector
c of deprivation counts is compared against a
cut-off k to identify the poor, where k = 1…d.
Hence, the identification method ρ is defined as
ρk (yi;z) = 1whenever ci ≥ k, and ρk(yi;z) = 0
whenever ci < k. Finally, the set of children who
are multidimensional poor is defined as zk= {i :
ρk(yi;z)}.Inother words, the method identifies
as poor any child who is deprived in more than
k number of dimensions. Alkire and Foster
(2014) refers toρk as a dual cutoff method
because it first applies the within dimension
cutoff zj to determine who is deprived in each
dimension, and then the across dimension
cutoff k to determine the minimum number of
deprivations for a child to be considered
multidimensional poor.
They identify absolute poverty as those children
who suffer from at least two or more
deprivations (equivalent to k = 2), and as in
severe deprivation those who suffer from at
least one deprivation (equivalent to k=
1).Naturally, the decision regarding the across
dimension cutoff depends on various factors
including the number and type of indicators
involved in the analysis. The Alkire-Foster
method formulates more explicitly the dual
cutoff method and allows us to compare the
results according to different cutoff values in
order to carry out sensitivity analysis.The first
measure to consider is the headcount ratio or
the percentage of children that is poor. The
headcount ratio H= H(Y;Z) is defined by:
H=Q/N………………………………………………………………
……….(1)
WhereQ= Q(y;z)is the number of children in the
set zk, as identified usingρkthe dual cutoff
method.
Alkire and foster (2011) proposed a headcount
measure that is adjusted by the average
number of deprivations experienced by the
poor. To this end, a censored vector of
deprivation counts ck is defined so that if ci ≥ k,
then ci (k) =ci; and if ci< k, then ci(k) =0.This is
to say that in c(k) the count of deprivations is
always zero for those children that are not poor
according to the ρk dual cutoff method, while
children that were identified as poor keep the
original vector of deprivation counts ci . Then, ci
(k)/d represents the shared possible
deprivations experienced by a poor child i, and
hence the average deprivations shared across
the poor is given by:
A
=
𝐜𝐢(𝐤)/𝐝
………………………………………………………………
Q
(2)
By focusing on the poor the Alkire – Foster
approach allows computing a final adjusted
headcount ratio that satisfies the properties of
decomposability and poverty focus. The
(dimension) adjusted headcount ratio M0 (y ; z )
is given by:
M0
=
HA……………………………………………………………………
…………………. (3)
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Based on previous literatures and the recent
poverty cutoff,k. The dual cutoffs in this
agreed up on agenda, sustainable development
approach are quite different from one another.
goals Alkire and Santos (2010), UNICEF (2015),
The choice of k could be a normative one, with
Plavgo, et al (2011), (Dr. Tassew, 2012), three
k reflecting the minimum deprivation count
dimensions were included in the MPI: health,
required to be considered poor in a specific
education, and the standard of living are
context under consideration. There may also be
selected for Ethiopia. They have been chosen as
a role for empirical evidence in the setting of
there is consensus that any multidimensional
kafter determining the indicator cut-offs, the
poverty measure should at least include these
Alkire-foster method attaches weights to each
three dimensions; for the ease of
deprivation. The MPI weighs each dimension
interpretability; and finally for reasons of data
equally (1/3) and within each dimension, each
availability. Whether a child may be considered
indicator is weighed equally. The weighted
deprived in each indicator is, largely for reasons
deprivations are then summed up, and the
of data availability of some of the indicators,
cross dimensional cut-off is applied. The MPI
determined at the household level (Santos,
uses a cross-dimensional cut-off of 1/3. Hence,
2010). For the purpose of this study, however,
a school aged child is multidimensional poor, if
the researchers have added more dimensions
it’s weighted deprivations sum up to 1/3 or
based on the environment and the economy of
more. This study uses equal weights to all
the town.
dimensions (UNICEF, 2015).
In this methodology, the researchers
considered the deprivation cutoffs zj and the
TABLE 1: DIMENSIONS AND DEPRIVATION CUT-OFFS
Dimensions
1. Water(Wi)
1.
Education (Ei)
Indicators
Child is deprived if……
Weight
Safe drinking water …she/he is living in the household whom source of 1/6
Hi1)
drinking water is unprotected, river/dam/pond
and time to get drinking water source is more than
30 minute (SDG 6 Clean water and sanitation)
School attendance
…she/he is not attending primary school/no 1/12
education (SDG 4 Quality of education)
Years of education
2.
Housing (Hi)
….no household member of the considered child 1/12
has no at least five years of education(SDG4
Quality of education)
Main floor material …she/he is living in the family where the house is 1/12
(Hsi1)
made of dung ,mud, sand dirt its number per room
is greater than or equal to three( SDG11
Sustainable cities and Communities)
Type of roof of the …the
roof
of
the
house
is
non- 1/12
house (Hsi2
corrugated/cement(SDG11 Sustainable cities and
Communities)
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3.
Sanitation (Si)
Toilet facilities
….she/he is living in the household where the type 1/6
of toilet is not flush/ventilated and it is shared
with another households(SDG 6 Clean water and
sanitation)
4.
Information (Ii)
Access
information
5.
Asset
Access to use asset
6.
Freedom
Free from child labor
to …..she/he is living in the household who has no at 1/6
least radio, television, and telephone
…….she/he is not living in the household who has 1/6
no more than one refrigerator, bicycle, motorcycle
or a car( SDG1 No poverty)
...she/he is doing business beyond his/her age 1/6
limit
3. Result and Discussion
townschool aged-children are in adult age
3.1. Demographic characteristics of School
group. Out of the total children considered for
aged children
this analysis the average age of a child is 11
According to the primary data we have
years old during collection of the survey. And
collected, the majority of Dambi Dollo town
the size of household in Dambi Dollo town
household heads in where children between 7
where the school aged-children were dwelling is
and 15 years old are dwelling is male and their
6 members, on average. For more see figure 2
average age is 44 years old. This shows that the
and table 3 below
average age of the heads of households of the
Figure 1: Child distribution by its sex
child distribution by sex
1023
Female ,
47.63%,
Male, 52.37%
Female
Male
Source: Authors calculation from the survey, June 2021
TABLE 2: SUMMARY STATISTICS OF MAIN VARIABLES
Variable
Mean
Std. Dev.
Min
Age of head of household
44.15351
13.29505
14
Age of child
10.9557
2.612398
7
Household size
6.086303
2.549122
1
Source: Authors calculation from the survey, June 2021
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Workneh Girma et al/ Assessment of Multidimensional Child Poverty in Ethiopia: The case of Dambi Dollo town, Oromia Regional State
3.2. Distribution of School Aged-Child and
dimensions they have experienced
Out of the total 288 observations of Dambi
Dollo town school aged-children, majority of
them ,35 percent , are deprived in 3 dimensions
followed in 4, 1, 2, 5, and 6 out of six selected
dimensions accounting for 27,13,12, 9, and 1
percent of respectively. And only 3percent of
the total children taken into account for this
analysis are not deprived in any dimensions or
by zero dimensions. This is similar with the
previous finding by Plavgo.et al. (2013) on the
“Multidimensional child deprivation trend
Analysis in Ethiopia” using under five child as a
unit of analysis and employing the multiple
overlapping deprivation (MODA) approach
which found that a very few percentage of
under five children in Ethiopia were deprived in
none of selected dimensions identified by them
and 75 percent of them are deprived by more
than two dimensions. From the following table
one can observe that majority of school agedchildren in Dambi Dollo town are deprived by
more than two dimensions. See figure 4 below
number of dimensions
FIGURE 2 : PROPORTION OF DEPRIVED CHILD IN DIFFERENT DIMENSIONS
1.15
7
6
6
8.91
5
5
26.78
4
4
34.75
3
3
12.25
2
2
12.68
1
1
0
0
3.49
10
20
30
40
percentage of children deprived in specified dimensions
percentage of children
dimension
Source: Authors calculation from the survey, June 2021
3.3. Child Characteristics by Their Deprivation
focus is on these who are multidimensionally
Status
poor based on 33percent of the poverty cut-off
From the following figure it is shown that 25
to estimate the incidence, intensity and breadth
percent of the Dambi Dollo town school agedof their multidimensional poverty. Estimate
children are non-deprived from the six selected
results of these MDP indices are presented in
dimensions and the remaining 75 percent are
next the sub-section of this chapter.
identified as deprived. After this ward, our
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Workneh Girma et al/ Assessment of Multidimensional Child Poverty in Ethiopia: The case of Dambi Dollo town, Oromia Regional State
Figure 3: Identifying the non-deprived and deprived percent of school aged-child
deprivation status of the children
25%
75%
non-deprived
deprived
Source: Authors calculation from the survey, June 2021
3.4. Multidimensional Dambi Dollo town
School-Aged Child Poverty Estimate
The multidimensional child poverty estimate is
based on the six selected dimensions as health,
education, access to basic information media,
housing (shelter), sanitation , and care (child is
not living either with mother or father). Equal
weights are applied to each indicators and dual
cut-off poverty used and all the AF (2011, 2011)
steps are followed to identify the
multidimensionally poor child. Child here and
after wards refers to a child whose age is
between 7 and 15 residing in the Dambi Dollo
town regions of Ethiopia.
The minimum
number of dimensions (Poverty cut-off, k) by
which a child should be deprived to be
identified as multidimensionally poor. Incidence
(H0), the intensity (A) and breadth (M0) of child
poverty are indices presented in this subsection..
The head count ratio shows the proportion of
poor children that are multidimensionality poor
based on the poverty cut-offs. Out of the total
identified deprived children in Dambi Dollo
town Ethiopia, majority of them are deprived in
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one to six followed by two to six, three to six,
four to six and five to six with the head count
ratio of 97%, 87%, 76%, 40%, and 11%
respectively. From table 4, one can observe that
the incidence of child poverty decreases with
the level of poverty cut-off. Based on the AF
methodology, a child is considered to be
multidimensionally poor if its deprivation score
is more or equal to one third of weighted
selected total dimensions (Alkire.et al, 2015).
The result of MDP estimate of the proportion of
children that is multidimensionally poor is 87%.
However, the head count ratio does not reflect
the extent of poverty among the deprived
rather than counting the percentage of children
who are multidimensionally poor. We could not
know that whether all poor children are
deprived in all considered dimensions or the
degree of their deprivation with this index. This
question is answered by the average
deprivation ratio which is presented in the 3rd
column of table 4. The results suggest that a
poor child is deprived by 58% of the weighted
dimensions, on average. This revealed that the
average poor child is deprived by more than
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Workneh Girma et al/ Assessment of Multidimensional Child Poverty in Ethiopia: The case of Dambi Dollo town, Oromia Regional State
half of the considered weighted dimensions,
about 4 dimensions. This child may be
deprivation in health, education, sanitation and
access
to
basic
information
media
simultaneously or care, housing (shelter),
health, and information dimensions or the
other combinations of dimensional deprivation
together. Column 5th of table 4 shows that the
average deprivation of weighted indicators is
increasing with the level of poverty cut-off.
Moreover, the intensity of multidimensional
school aged-child poverty in Dambi Dollo town
regions of Ethiopia is also increasing with the
level of poverty cut-off and it is 100% when k =
6 .i.e. the child is multidimensionally poor in all
the considered dimensions.
Thus, the head count ratio must be adjusted to
the average deprivation ratio to show the
breadth of multidimensional child poverty.
Column 4th of table 4 represents the
multidimensional poverty index of Dambi Dollo
town school aged-children in Ethiopia. It reveals
that the multidimensionally poor children in
Dambi Dollo town Ethiopia, on average,
experiences 50percent of the weighted
deprivations out of the six selected dimensions.
One can note from table 4 that the MPI is
decreasing with k level but the intensity of
poverty is increasing. This is due to the effect
that the percentage number of poor child is
decreasing at an increasing rate while the
intensity of child poverty is increasing at a
decreasing rate relatively.
TABLE 3: ESTIMATES OF CHILD MDP INDICES
K
H0
A
M0=A*H0
Average deprivation
K=1
0.971
0.535
0.519
3.21
K=2
0.868
0.582
0.502
3.492
K=3
0.759
0.614
0.466
3.684
K=4
0.395
0.719
0.284
4.314
K=5
0.110
0.855
0.094
5.13
6
0.014
1.00
0.014
6.00
Source: Authors calculation from the survey, June 2021
Decomposition of multidimensional adjusted
ranking is also similar for the proportion of
head count ratio of Dambi Dollo town Ethiopian
multidimensionally poor child in respected
school aged-children by the dimensions made
dimensions which is represented by the head
as it helps to identify the sector to be targeted
count ratio (H0) under the column 2nd of the
by the policy makers to eradicate child poverty
table. This shows that among the selected
and cutting its transfers to the next age group in
dimensional deprivations, the Dambi Dollo
the future. Table 5 below implies the
town school aged-children are being deprived
contribution of each dimension to the
mostly from these three dimensions.
aggregate multidimensional poverty index. The
The housing dimension includes overcrowding
multidimensional poverty index of Dambi Dollo
and appropriate type of roof of the house
town’s children whose age is between the range
indicators. As the result of the H0, it is indicated
of 7 and 15 is 0.502.
that from the total multidimensionally poor
The decomposition of this index is represented
children in Dambi Dollo town Ethiopia, 48% of
under column 4th of table 5 both in absolute
them are deprived in health and housing, and
and relative contribution. The highest
23% are deprived in access to basic information
multidimensional deprivation out of the
media, and the remaining 16% are deprived in
selected variable is estimated for the housing,
other dimensions.
The decomposition of
health, and access to basic information media
multidimensional child poverty adjusted head
followed by care, sanitation and education
count ratio estimate revealed that an average
dimensions. They account for 27%, 26%, 26%,
multidimensional poor child is deprived by 39%
and 9%, 7%, and 5% relative contribution for
(each equally) of housing, health and
the multidimensional child poverty index. This
information dimensions and by 11% of the
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remaining three. Thus, housing, health and
access to basic information media, are the
policy target dimensions to reduce the
multidimensional child poverty in Dambi Dollo
town. See table 5 below.
TABLE 4: DECOMPOSITION OF MULTIDIMENSIONAL CHILD POVERTY INDICES
- H0 index
- M0 index
Absolute
Relative Contribution Absolute
Relative contribution
Contribution
contribution
Sources
1: health
0.235
0.271
0.132
0.263
2: housing
0.236
0.27
0.133
0.265
3: education
0.040
0.046
0.026
0.052
4:information
0.231
0.267
0.131
0.261
5: sanitation
0.048
0.055
0.033
0.066
6: care
0.077
0.089
0.047
0.093
0.868
1.000
0.502
1.000|
Total
Source: Authors calculation from the 2021survey
4.2.2.1. The relative contribution of
basic information media (information) relative
dimensions to the Alkire and Foster (2011)
to the other selected dimensions respectively.
MDP index estimated at population level
While 79percent is funded by these dimensions
(results in percent).
ranked above, the remaining 21percent of the
More than half of multidimensional school-aged
MPI is contributed from care (partial orphan
child poverty index in Dambi Dollo town is
hood or full), sanitation, and education (no
contributed by housing, health, and access to
education).
FIGURE 4: DECOMPOSITION OF MPI
relative contrbution in%
30
25
20
15
26.26
26.5
26.09
10
5
6.63
5.22
9.29
0
health
housing
Education
Information
Source: Authors calculation from the 2021survey
The multidimensional child poverty indices are
also decomposed between male and female
Sanitation
Care
child and their respective deprivation incidence
and intensity is estimated. Table 7 below
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Workneh Girma et al/ Assessment of Multidimensional Child Poverty in Ethiopia: The case of Dambi Dollo town, Oromia Regional State
represented population share, the proportion
children are identified as multidimensionally
of child poverty by their sex, the level or extent
poor and deprived, on average, in 3.468
of their deprivation and the average dimensions
dimensions. This shows that an average school
deprived in. Among the total number of female
aged-male and female child in Dambi Dollo
children observations considered for this
town are almost equally deprived in
analysis, 87% of them are multidimensionally
multidimensional poverty. Thus, both are the
poor and deprived, on average, in 3.474
target because no difference is observed from
dimensions. Whereas, out of the total female
the estimated result. See table 7
child observation undertaken, only 86% of male
TABLE 5: CHILD MDP INDICES’ DECOMPOSITION BY SEX
Group
Population H0
A
M0=H0*A
Average
share
deprivation
Female
0.478
0.874
0.579
0.506
3.474
Male
0.522
0.863
0.578
0.499
3.468
population 1.00
0.868
0.578
0.502
3.468
Relative contribution of children by their sex to the AF 2011 MDP indices
Group
Female
0.481
Female
0.482
Male
0.519
Male
0.518
Source: Authors computation fromthe primary data, June 2021
Table 8 represented the multidimensional child
dimension .i.e. in 3.432 dimensions. Whereas,
poverty by the sex of Dambi Dollo town
86percent of children living household headed
household head where the child is dwelling.
by male are multidimensionality poor and
Accordingly, out of the total observations in
deprived, on average, in 3.54 dimensions.
Dambi Dollo town children living in the
Therefore, school aged-children in Dambi Dollo
household headed by the female, 87percent of
town living with male headed household are
them are multidimensionally poor and an
more multidimensionality poor than these living
average child in this household is deprived, on
with the female head household, as indicated
average, in 57percent of the total selected
by M0. See table 8
TABLE 6: AF (2011) MDP INDICES DECOMPOSITION BY SEX OF HOUSEHOLD HEAD
Group
Pop. Share
H0
A
M0
Female head
0.686
0.870
0.572
0.498
Male head
0.314
0.863
0.590
0.510
Population
1.000
0.868
0.578
0.502
Absolute contribution
Female
0.596
Female
0.342
Male
0.271
Male
0.160
Relative contribution Female
68.72
Female
68.04
(in percent)
Male
31.28
Male
31.96
Source: Authors calculation from the survey, June 2021
The incidence of multidimensional Dambi Dollo
Table 9 shows this in detail. The following table
town’s child increases from young to adult and
shows that out of all the Dambi Dollo town
decreases from adult to old head of household
school aged-children dwelling in the household
age group accounting for 89, 88 and 85 percent
whose head is young, 89 percent of them are
of poor children in each category respectively.
poor in multiple dimensions and among these,
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Workneh Girma et al/ Assessment of Multidimensional Child Poverty in Ethiopia: The case of Dambi Dollo town, Oromia Regional State
the average child is deprived, on average, by
the 60 percent of considered weighted
dimensions or in 3.570 dimensions out of the
selected. This is followed by the children who
are living in the household headed by the adult
age category who are deprived, on average, in
3.522 dimensions. In contrary, 85percent of the
Dambi Dollo town school aged-child living in the
household headed by old age are poor in many
dimensions and deprived, on average, in 3.414
dimensions out of the total considered for this
analysis. Thus, children with the young head of
household in Dambi Dollo town are
multidimensional poor experiencing 53 percent
of all the selected dimensions. Here, the
population share of the child headed household
is very small (almost zero) but the intensity of
their poverty extent is high relatively.
Moreover the result suggests that as the age of
household head increases from young to old,
the breadth of multidimensional poverty (the
adjusted head count ratio) decreases from 53%
to 48%.
TABLE 7: DECOMPOSITION OF AF (2011) CHILD MDP INDICES BY THE HOUSEHOLD HEAD AGE GROUP
Group
H0
M0 =H0*A
A
Average
deprivation
1: Child
0.667
0.222
0.3320
1.992
2: Young head
0.885
0.527
0.595
3.570
3: Adult head
0.883
0.518
0.587
3.522
4: Old head
0.850
0.484
0.569
3.414
Population
0.868
0.502
0.578
3.468
Source: own calculation from the survey, June 2021
4. Conclusion and Recommendation
male children estimated being multidimensional
This research is entitled in the assessments of
poor. Their average age is 11 years old and
multidimensional child poverty Dambi Dollo
most of them are living with adult household
town, with the objectives of assessing the main
head of 44 years old, on average.
deprived
dimension,
the
incidence,
According to the estimation results of the
intensity/breadth of multidimensional school
incidence of multidimensional poverty index,
aged-child
poverty
employing
the
87% of the total school aged-children in the
multidimensional poverty index (MPI) of the
town are identified as multidimensional poor,
Alkire and Foster (2011a) methodology.
on average. An average multidimensional poor
Based on the MPI estimation, 87% of the total
child in the town is being deprived in 58% of six
school aged-children are multidimensionality
selected dimensions, identified by intensity.
poor in Dambi Dollo town. However, the
Adjusting
the
incidence,
an
average
estimated multidimensional child poverty index
multidimensional poor child in Dambi Dollo
in Dambi Dollo town (M0) is 0.502. Showing
town is deprived in 50.2% of the total selected
that average school aged-child is deprived in
dimensions. This implies that MDP child is
50% the total six selected dimensions. The
deprived in 3.48 dimensions out of six selected.
estimated intensity of their poverty is 0.58
The highest (27%) relative deprivation for these
which implies that a multidimensionality poor
children is contributed by the housing
child in Dambi Dollo town is deprived in 3.48
dimension which includes an inappropriate type
dimensions out of the total considered
roofing material (no-corrugated/non-cement)
dimensions, on average. Among the total school
and overcrowdings (a child is living with
aged-child considered for this analysis, majority
household where the number of household
of them are male and 48% of them are females.
member per sleeping room is more than three)
Out of total female children in Dambi Dollo
followed by the health dimension (26%) with
town, 87% of them are identified as
indicators of unprotected source of drinking
multidimensionality poor whereas 86% of total
water and indoor air pollution or child is
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dwelling in the household who has no safe
kitchen and prepare food in room using wood,
shrubs, animal dung and has no electric mitad.
The third (26%) dimension that a Dambi Dollo
town school aged-child in Dambi Dollo town
being deprived in is access to information media
which implies that an average MDP child is
living in the household that has at least no
access to radio, TV, and telephone.
Unable to get care/love contributed the fourth
relatively which is measured by the relationship
to the household head. Deprived in care implies
that the child is either partially orphan or have
no both mother and father. It is common sense
here that mother and father are the care for
their children assuming it is their responsibility.
Generally, a school aged child of Dambi Dollo
town is being deprived in housing, health,
information, care, sanitation, and education
dimensions respectively with the incidence of
poverty (H0 = 0.868) and the intensity (A=0.58
) and the multidimensional child poverty
adjusted head count ratio(M0) is 0.502 at the
poverty cut-off, k=2.
Based on obtained findings, the following policy
implications are forwarded.
 Effective understanding of child poverty
needs to consider poverty in itself and
the main drivers of multidimensional
child poverty. Actions which lift children
out of poverty by giving their families
access to resource and basic needs
through increasing welfare support and
increasing
employment
shall
be
undertaken by the concerned bodies.
 Actions targeted both at the children
themselves and at their wider
environment including their family and
the whole community in which the
children are living shall be undertaken to
increase the likelihood that the poor
children are able to escape poverty when
they grow older and older and to reduce
the intergenerational transmission of
poverty to their own children. And this
may be done through improving access to
health and education, directing resources
to children and their families, seeking to
influence parental fertility and marriage
so that the early marriage reduced and
household size which increases the
likelihood of child being poor be reduced
to less than the average. All concerned
bodies shall work on the provision of
basic need services to decrease a
likelihood of the next child being
deprived in these dimensions.
 Provision of aid and supportive
development programs that focuses on
affected children in general and street
children and orphan hoods in particular
may be the way out for some in the short
run period of time. We highly
recommend that all concerned body shall
establish rehabilitation center for those
children.
 Moreover, promoting gender equity both
in household head and children in access
to resources may be important aspects of
antipoverty policy for children and to
address the likelihood of being
multidimensional poor observed in
gender difference. In order to achieve
this strong leadership and commitment
across the whole public sector is highly
recommended.
 Developing public early years (Pre-school)
educationin the town so as the poor will
get access to it.
 Thus, child rights need to be addressed
through
specified
child-targeted
programs as well as mainstreamed into
macroeconomic and social sector
development policies.
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