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1. Nuhu Bamalli Polytechnic Multidisciplinary Journal 1 :( 1) 145-162 Barnabas et al., (2016)
EFFECT OF MILLENNIUM VILLAGE PROJECT ON LIVELIHOOD OF FARMERS
IN BENEFICIARY COMMUNITIES OF KADUNA STATE, NIGERIA.
Barnabas T. M.,1
Akpoko J. G.1
Akinola M. O. 1
and Nasa’i D. H.2
1
Department of Agricultural Economics and Rural Sociology, Ahmadu Bello University, Zaria,
Nigeria.
2
Department of General Studies, Nuhu Bamalli Polytechnic, Zaria, Nigeria.
ABSTRACT
This study assessed the effect of the Millennium Village Project (MVP) on livelihood of farmers in
beneficiary communities of Kaduna state. The study specifically investigated the socio-economic
characteristics of the beneficiaries of the project; examined the level of implementation of the
project and its impact on the benefiting farmers in the study area. Structured questionnaire
schedule was used to collect Information from 120 benefiting farmers in the 28 settlements of the
study area. Descriptive statistic supported by Lorenz Curve and Gini Coefficient were used to
analyze the data. The findings showed that most of the beneficiaries were young adults between
the ages of 31-40 (36%) and had access to 72% of the MVP facilities. The analysis of Gini
coefficient indicates that income disparity among the beneficiaries reduce from 15% in 2006 to
6% in 2011. Similarly, the finding reveals that the mean income of the sampled respondents rose
from N240, 535 before the project to N291, 017 after the implementation of the project. It is hereby
recommended that government should encourage MVP project to be replicated in other non–
participating communities of the state; so as to reduce poverty.
Key words: Farmers, Livelihood, Poverty, Millennium village project.
INTRODUCTION
Poverty is a general phenomenon that has been globally recognized as a threat to the survival of
mankind. In line with this realization the United Nation declared the year 1996 as the international
year for the eradication of poverty (Ozigbo, 2001). It is a phenomenon that affects the physical,
moral and psychological condition of man. It manifests in different ways and in all facets of human
life; low income, isolation, powerlessness, vulnerability, physical weakness and lack of resources
(Chamber, 1983 and Dixon, 1990).
However, scholars differ in their conceptualization of the phenomenon. Sen (1983) sees poverty
as a deprivation reflected in inadequacy of social and political rights, economic exclusion and the
collapse of services in rural areas which makes it difficult for rural dwellers to fully exploit their
life potential for personal development and for self-actualization. Reducing the incidence of
poverty among the population has received increased momentum at national and international
levels (Butler and Mazur, 2004). The most afflicted are the rural poor who constitute over 70 % of
the poor and are employed in agricultural production (Olatonbasun, 1975). Rural poverty is
therefore, the inability of rural people to meet basic and material needs and deprivation in social
and political rights, reflected in economic exclusion and the absence or collapse of services in rural
areas (Sen, 1983).

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The task of poverty reduction has been the concern of preceding governments in Nigeria. Quite a
number of programmes were initiated by government to address the incidence of poverty in the
country. Among these programmes are: Operation Feed the Nation, Green Revolution, Directorate
of Food Roads and Rural Infrastructure, Better Life for Rural Women, Family Support
Programme, National Economic Empowerment and Development Strategy, among others. In spite
of Government’s efforts and goodwill to reduce poverty in the country, it has continued to rear its
ugly heads in rural areas. Butler and Mazur (2004) have observed that African development, which
is lagging behind that of Global South despite decades of assorted development approaches has
been receiving increased attention as the United Nation’s Millennium Development Goals provide
the goal for international development effort through 2015.
The Pampai’da project which was introduced in 2006, is one of the United Nation’s millennium
goals aimed at; providing farm inputs, reducing the incidence of ill-health as a result of preventable
diseases, increase literacy level and improving the quality of life (through provision of good
drinkable water, roads electricity), ending poverty and hunger, gender equity, child and maternal
health, combat malaria and HIV Aids, among others. There is equally the need to assess or evaluate
at each stage of the project, whether it can be redesigned or repackaged to meet up with emerging
challenges. The study would therefore, provide useful information and serve as reference point to
researchers and policy makers interested in poverty reduction in Nigeria.
METHODOLOGY
This study covered 28 settlements (Pampai’da) under Saulawa District in Ikara Local Government
Area of Kaduna State. The study area is approximately 160km away from Kaduna (the capital of
Kaduna State). The population of Pampa’ida settlements in 2011 based on the 2006 census is
projected to be 8066 at a growth rate of 2.5 per annum when this study was conducted. The main
activity carried out in these settlements is agricultural production, and the main crops grown in the
area includes maize, sorghum, millet, rice, and cowpea. Livestock and animal husbandry is widely
practiced in the area. The millennium village project was implemented in Pampa’ida which
comprises of 28 settlements having 952 households. For the purpose of this study the 28
settlements were grouped into 4 clusters of 7 settlements each, based on their proximity to each
other. In each cluster 12% of the household members were randomly selected to obtain the 120
respondents for the study.
The study is Quasi-experimental and used both primary and secondary sources of information. The
primary data were collected through the use of structured questionnaire schedule and two check
lists for the key informants (i.e the ward heads as Opinion Leaders and one official of the MVP).
Descriptive statistics (percentages, frequency counts and mean) were used to achieve the
objectives of the study.
The Gini coefficient is a measure of inequality of a distribution. It is defined as a ratio of values
between 0 and 1: the numerator is the area between the Lorenz curve of the distribution and the
uniform distribution line; the denominator is the area under the uniform distribution line. The
coefficient varies between 0, which reflects complete equality and 1, which indicates completes
inequality (one person has all the income or consumption, all others have none).

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RESULTS AND DISCUSSION
Socio-economic Characteristics of the Beneficiaries
The result of data analysis as shown in Table 1 indicates that 32% of the beneficiaries are between
the ages 21-30, while 38% fall between 31-40years of age. The result equally shows that 20% of
the beneficiaries are between the ages of 41-50, while only 10% are above 50 years of age. From
this analysis, it is evident that the average age of the beneficiaries was 36 years. Age is a very
important factor in agricultural production because it determines the physical strength of the farmer
(Mohammed, 2010). This result also agrees with the work of Alabi et al. (2005), in which they
found that majority of the beneficiaries of MVP were of middle age in a study of resource
productivity and reforms on maize production. Rahaman et al. (2002) reported that farmer’s age
may influence adoption of innovation or technology in several ways. This implies that the
population is a youthful and energetic one which can be utilize in agricultural production.
The result in Table 1 equally shows that majority (88%) of the beneficiaries were males, while
12% were women. This can be attributed to the fact that household heads are mostly men except
in a situation where the husband is dead or the woman is a divorcee. Okoye et al. (1991) reported
that most small scale farmers in Nigeria are male and married.
Education variable was also examined and the result in table 1 shows that most of the beneficiaries
did not have formal education as more than half (58%) did not attend formal educational
institution. Less than 1% of the respondent had adult education; while 27% attended primary
school, and both secondary and tertiary institutions had 7% each. The education level in the study
area is very low, with one primary school which was established about 30 years ago. This result
reveals low literacy rate in western education in the study area.
Household size as depicted in table 1 reveals that 56% have a household size of 1-5, while 32%
has a household size of between 6 -10, 6% of the beneficiaries have between 11-15 persons per
household, and 5% have between 16-20. Less than 1% has a household size of more than 25
persons. This analysis implies that the average household size of the beneficiaries was 6. This
could be attributed to the fact that the area is predominantly farmers and the culture of early
marriage in the rural areas is widely practiced so one is not surprised at the small size of the
households. Household size in an agrarian society plays an important factor because it influences
to a large extent supply of labor for immediate farm need.
The study also investigated marital status and the result as shown in table 1 indicates that 6.5%
were single, 86% married, 5% divorced and 2.5% widowed. The reason for the high percentage of
the beneficiaries being married was because the research focused mainly on household heads that
were married before widows, divorcees and others.
With respect to farm size, table 1 reveals that 16% of the beneficiaries have farm size of less than
2 hectares, 55% have 2-4 hectares of farm, while 29% have farm size above 4 hectares. This shows
that the beneficiaries are small size farm holders with an average of 4 hectares. Farm size in an
agrarian society is an important resource to fight against poverty and improving living conditions
of the farmers.

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Farming experience is an important factor in agricultural production. It is assumed that the higher
the experience of the farmer the better his productive capacity. That is to say that experienced
farmers are most likely to make sound decisions that will increase their productivity. It was
observed that 5% of the beneficiaries have 1-10 years of farming experience, 42% have 11-20
years experience in farming, 36% have 21-30 years of farming experience, while 17% have 31 and
above experience in farming. This analysis implies that the average farming experience of the
beneficiaries was 20 year. This revealed why the beneficiaries readily adopted the programmes of
the millennium village projects. The more the experience in farming, the more farmers are less
likely to oppose the adoption of new technologies as farming performance of farmers could have
great influence on their participation (Nkonyo et al., 2008).
MVP Awareness
The result in Table 1 indicates that 61% of the beneficiaries became aware of the MVP through
the MVP officials, who gathered them for a meeting and told them about the project, 4% came to
know about MVP through radio and television, 9% through their friends and 16% through their
family members. Awareness about a project or innovation plays a major role in the adoption of
such project or innovation.
Table 1: Socio-economic Characteristics of Beneficiaries
Variable Frequency Percentage (%)
Age
21-30 38 32
31-40 46 38
41-50 24 20
51-70 12 10
Gender
Male 106 88.0
Female 14 12
Education
No formal education 36 30
Koranic 34 28.0
Adult education 1 0.8
Primary school 33 27.2
Secondary school 8 7.0
Tertiary institution 8 7.0
Household size
1-5 67 56.0
6-10 39 32.0
11-15 7 6.0
16-20 6 5.2
21-25 0 0
26-30 1 0.80

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Variable Frequency Percentage (%)
Marital status
Single 7 6.5
Married 104 86.0
Divorced 6 5
Widowed 3 2.5
Farm size
Less than 2 19 16.0
2-4 66 55.0
Above 4 35 29.0
Farming experience
1-10 6 5
11-20 50 42.0
21-30 43 36.0
31-40 19 17.0
MVP Awareness
Pampa’ida official 74 61.0
Radio and Television 4 4.0
Friends 23 19.0
Family 19 16.0
Mode of land Acquisition
Inheritance 111 92.5
Government allocation/Purchase 6 5
Gift 3 2.5
Lease 0 0
Rent 0 0
Loan 0 0
Frequency of contact with ext. workers
1-10 24 21.0
11-20 32 28.0
21-30 14 12.0
31-40 16 14.0
41-50 14 12.0
51 and above 13 13.0
Total 120 100
Frequency of Contact with Extension Workers by Beneficiaries
The result in Table 1 indicates that 21% of the beneficiaries reported that they had between 1-10
contact periods with MVP extension workers, 28% had 11-20 contact periods, 12% had between
21-30 periods, 14% had between 31-40 contact periods, 12% had between 41-50 periods of
contact, while only 13% reported that they had more than 50 contact periods with extension
workers. This analysis revealed that the beneficiaries had an average of 30 contacts with extension
workers during period of assessment. Extension service is closely linked with adoption of new

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technology because the extension workers can offer advices and suggestions to the farmer on more
regular basis.
Level of Implementation of the Project and Access by the Beneficiaries
The second objective of the study was to examine the level of project implementation and access
by the beneficiaries. It was found that the beneficiaries had access to all the activities of the MVP
(such as drugs, farm inputs, electricity and roads, portable water which improve the quality of life
in the affected settlements) at varying levels as shown below:
Health Clinic and Provision of Drugs
The analysis presented in Table 2 reveals that 16% of the beneficiaries’ family members attended
the health clinic whenever they fell sick. The MVP built a clinic and renovated 3 other health care
centers and stocked them with drugs and materials. The presence of this clinic and the health centre
encouraged them to go to the clinic whenever there was an illness and the women attended ante-
natal check-up, unlike in the past where they had to go to a distance of 10km to get any medical
attention. The presence of qualified staff that often went from house to house to provide health
services to the people and an ambulance helped increased vaccination, hence reduction in infant
mortality. This was to meet MDG targets 4, 5 and 6.
Similarly, the result presented in Table 2 reveals that 15% of the beneficiaries reported that they
got drugs free from the clinics and really motivated them into the activities of the MVP. As a result
of the provision of free drugs, most of the people were encouraged to administer vitamin A
micronutrients to their children, they started home treatment of diarrhea and the women started
accepting family planning services. This was to meet MDG targets 4, 5 and 6, which deal with
child health, maternal health and combat malaria and HIV/AIDS.
Provision of Access Road and Electricity
The analysis of result presented in Table 2 shows that 6% of the beneficiaries had access to good
road. This is so, because the 10 km tarred road constructed by the MVP passes through some
settlements to Pampa’ida Makaranta which serves as the headquarter of the 28 settlements that
make up the study area, the rest of the settlements do not have tarred (Tarmac) road but were
graded in some places to make movements of goods and services easier. It was found out from this
study that only 2% benefitted from electricity since it is only Pampa’ida Makaranta that has such
amenity provided by the MVP. It could be observed that as a result of the electricity in Pampa’ida
Makaranta, there was a shop where hand-sets batteries could be charged at a fee. This in itself is
another source of employment and income generation thereby reducing poverty, which was to
meet MDG target 1.
Provision of Treated Mosquito Nets
The result depicted in Table 2 shows that 17% of the beneficiaries reported that they were given
treated mosquito nets (one to every member of the household). This was to meet MDG 6, which
is to combat malaria and HIV/ AIDS. The provision of the nets went a long way in reducing the
prevalence of malaria in the area from about 28% in 2006 to just 10 % in 2011 when this survey
was carried out.

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Provision of Portable Water
The analysis of result presented in Table 2 also reveals that 9% of the beneficiaries reported that
there were 2 solar powered boreholes and other hand-pumps boreholes dug by the MVP in nearly
all the settlements under study thereby giving them access to good drinking water throughout the
year. This greatly reduced the distance they used to cover in order to fetch water to merely some
metres. This was in meeting MDG 1 target. However, there were some settlements that did not
enjoy such facilities and therefore had to fetch water from streams and rivers.
Provision of Farm Inputs and Storage Facilities
The result as presented in Table 2 shows that 15% of the beneficiaries reported that they got farm
inputs free from the MVP at initial start of the project, but were later given at subsidized prices.
The project provided high value and early maturing crops, and promoted the cultivation of rice,
soya beans, cowpea and groundnut which hitherto were not cultivated in commercial quantity.
This really increased not only their staple food as maize production increased from 1.0 t/ha in 2006
to 4.0 t/ha in 2011, their income also increased. The people had lesser months of hunger
(September-November) which they used to have before 2006. They also reported that as a result
of the subsidy, they were able to increase their farm sizes to twice their former farm sizes. This
was to meet the MDG target 1, which is ending poverty and hunger. The study equally reveals that
only 2% benefitted from the grain storage constructed by the MVP at Pampa’ida Makaranta and
training them in improved post harvest technologies which reduced their post harvest loses due to
pests and other storage diseases. This was to meet the MDG 1 target by reducing poverty and
hunger.
Education and Computer Training
Analysis of result presented in Table 2 shows that 7% of the beneficiaries reported that they
benefitted from the education intervention of MVP in their area. According to them MVP did not
only construct new class rooms at their 30 year old primary school which had only 2 class rooms
before, they also furnished it with tables and chairs. Additionally, over 10 junior primary schools
spread all over the settlements were also constructed by the MVP to cater for those children that
were not up to school age (nursery). The provision of educational materials free to the pupils
boosted the school population to about 2000 from less than 400 pupils before the MVP
intervention. The introduction of school feeding programme in which the community contributed
10 % of their harvest, firewood and volunteer women who served as cooks, greatly attracted the
children such that school enrolment increased by about 35%. This was to meet the MDG 2 target.
The study also reveals that the MDG project trained women and youths on various occupational
skills like soap and body cream making, tie and dye, Tomato paste processing, groundnut oil
processing etc. The beneficiaries were also given loans from the Banks through cooperative
societies. This really empowered the women and also gave them some levels of social inclusion in
the scheme of things. This was in meeting the MDG 1and 3 targets.In addition, the study also
shows that 2% had benefitted from the provision of V-sat, installation of a GSM mast and ICT
Centre. Students and pupils had training there, with Airtel as the only available network in the
study area. This was to meet MDG 8 target.

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Table 2: Level of Implementation of the Project and Access by the Beneficiaries
Frequency of Contacts with Extension Workers
Result presented in Table 2 further shows that 90% of the beneficiaries reported that they had
contact with extension workers regularly; this must have encouraged the beneficiaries’
participation in the MVP activities. At the start of the project the beneficiaries were having regular
meetings with the MVP officials; this motivated them in participating in all the activities of the
project.
Distribution of Beneficiaries based on the Facilities Provided according to Clusters
The result in Table 3 revealed that 17% of the beneficiaries in cluster A, 16% in cluster B, 14% in
cluster C and 14% in cluster D benefited from the health clinics respectively. Beneficiaries who
got drugs from the clinic free off-charge in clusters A, B, C and D were 17%, 16%, 16% and 15%
respectively. Clusters A, B, C and D beneficiaries reported that they benefited from access road at
4%, 2%, 4% and 6% respectively
Activities Frequency Percentage (%)
Health clinics 99 16.0
Drugs 98 15.0
Access roads 41 6.0
Treated mosquito nets 117 17.0
Farm inputs 110 15.0
Education 49 7.0
Electricity 16 2.0
Storage facilities 18 2.0
Portable water 77 9.0
V-sat and computer 15 2.0
Frequency of extension contact 80 9.0
Total 720 100

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Table 3: Distributions of Beneficiaries based on the Facilities Provided according to Clusters
Activities
CLUSTERS
A B C D
Freq % Freq % Freq % Freq %
Health clinics
Drugs
Access roads
Treated mosquito nets
Motorized water pump
Farm inputs
Livestock extension services
Electricity
Storage facilities
Portable water
V-sat and computer
Frequency of extension
contacts
28 17
26 17
8 4
30 18
5 3
28 16
13 7
0 0
3 2
15 4
0 0
19 12
20 16
19 16
2 2
21 17
4 3
16 13
10 8
2 2
3 2
15 12
3 3
7 6
34 14
35 16
10 4
35 16
10 4
35 16
19 8
5 2
10 4
10 4
10 4
19 8
27 14
28 15
11 6
36 20
4 2
36 20
7 4
0 0
2 1
22 11
0 0
15 7
Total 175 100 122 100 231 100 188 100
The analysis of empirical data as presented in Table 3 shows that 18% of beneficiaries in cluster
A, 17% in cluster B, 16% in cluster C and 20% in cluster D benefited from treated mosquito nets
while beneficiaries who benefited from motorized water pump were 3%, 3%, 4% and 2% for
clusters A, B, C and D respectively. Farm inputs gotten free or sometimes at subsidized price were
cluster A (16%), cluster B (13%), cluster C (16%) and cluster D (20%) while livestock extension
services 7% for cluster A, cluster B (8%), cluster C (8%) and cluster D (4%). Clusters A and D
had no electricity from the project while clusters B and C had 2% each. Storage facilities enjoyed
by cluster A and B recorded 2% each while clusters C and D had 4% and 1% respectively.
Beneficiaries in clusters A, B, C and D reported that the project had provided portable drinking
water at 4%, 12%, 4% and 11% respectively while clusters B and C had V-sat and computer at 3%
and 4% respectively whereas clusters A and D did not benefit. Contacts with extension agents was
12% for cluster A, 6% for cluster B while clusters C and D had 8% and 7% respectively.These
results show that the project had much effect on the people in the study area. The effect varies
from one cluster to the other, with cluster B having more benefits of the MVP facilities.

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Table 4: Gini Coefficient for MVP Beneficiries Farmers in 2011.
Class
Number
of
Farmers
%
freq of
Farmers
Cum % freq of
Farmers( X)
Total income
level Average income( Y)
%freq of
average income
( Y)
Cum % average
Income( Y)
Product of
Cum % freq of
farmers and
cum % of
average
Income (XY)
1000-40000 53 0.442 0.442 11427900 215620.75 0.016 0.016 0.006947
400001-800000 32 0.267 0.708 19948800 623400 0.046 0.061 0.012127
800001-1200000 10 0.083 0.792 10242500 1024250 0.075 0.136 0.006227
1200001-1600000 8 0.067 0.858 10787000 1348375 0.098 0.234 0.006558
1600001-2000000 6 0.05 0.908 10721400 1786900 0.130 0.365 0.006518
2000001-2400000 3 0.025 0.933 6752700 2250900 0.164 0.529 0.004105
2400001-2800000 0 0 0.933 0 0 0.529 0
2800001-3200000 1 0.008 0.942 3032100 3032100 0.221 0.750 0.001843
3200001-3600000 7 0.058 1 23985300 3426471.429 0.249 1 0.014581
Total 120 1 13708017.18 1 0.058906
Gini Coefficient 0.941094
The study also investigated the impact of the project on the beneficiaries. The result obtained from
the Gini Coeffecient as shown in Table 4 indicates a value of 0.94 in 2011. This implies that 94%
of the beneficiaries did not have income variability in 2011. This therefore means that only 6% of
the beneficiaries had disparity in their income level. This implies that the level of income
inequalities was narrowed as the gap income disparity was reduced.

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Table 5: Gini coefficient table for 2006
Class
Number
of
Farmers
%freq
of
Farmers
Cum % of
farmers
(X)
Total
Income
Level
Average
Income
% of
Average
Income
(Y)
cum % of
Average
Income(
Y)
Product
of Cum.
% of
farmers
and
Cum. %
of
Average
Income
(XY)
1000-400000 66 0.55 0.550 25800100 390910.6061 0.110 0.110 0.060469
400001-800000 41 0.342 0.892 32200100 785368.2927 0.221 0.331 0.075468
800001-1200000 4 0.033 0.925 207600 851900 0.015 0.345 0.000487
1200001-1600000 5 0.042 0.967 18500 1300700 0.001 0.346 4.34E-05
1600001-2000000 2 0.017 0.983 30100 1754050 0.004 0.351 7.05E-05
2000001-2400000 0 0 0.983 0 0.351 0
2400001-2800000 2 0.017 1 4617300 2308650 0.650 1 0.010822
2800001-3200000 0 0 1 0 1 0
3200001-3600000 0 0 1 0 1 0
Total 120 3555578.89 1 0.147359
Gini
Coefficient 0.852641
Lorenz curve 2006
Lorenz curve 2011
Line of Perfect Equality
Income
Cummulative%ofAverageincome(Y%)
1.0
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0
Cumulative percentage (X%)

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Figure 1: Graphical representation of Lorenz curve and Gini coefficient
The results in Table 5 shows that 85% of the beneficiaries did not have income variability in 2006
implying that 15% of the beneficiaries had disparity in their income. This finding reveals that after
the implementation of the MVP in the area, the income level of the beneficiaries shifted towards
the line of equality by 9%. Hence it can be adjudged that the project had enhanced the income of
the beneficiaries and by extension their poverty status.
Poverty Status
The poverty level of the beneficiaries in the study area before the MVP was about 50% with an
average individual income of N94.14k per day, but as a result of MVP intervention in 2006, the
poverty level reduced to about 46% with an average individual income of N113.90k per day.
Though this value was still lower than the World Bank indexing of 1 US Dollar (N155.00) per
day, yet, it can be adjudged that the MVP intervention had an effect on the standard of living of
the beneficiaries by reducing their poverty level.
Table 6: Mean Income before and after Intervention
Before After
Mean income N240,534.5 N291, 016.8
Variance 9.47E+10 2.78E+10
P-value 0’058*
T-value 1.65
The result presented in Table 6 reveals that the mean income of the individual beneficiary before
the project intervention was lower than their income after the project intervention. It shows N240,
535 and N291, 017 for 2006 and 2011 respectively. The mean income was significant at 10%
probability level. Based on this result it could be deduced that the MVP had positive effect on the
beneficiaries of the project. This implies that an increase in income of the farmer means improve
standard of living as it empowers the household economically and socially.
The study set out to assess the effect of the Millennium Village Project on the Livelihood of
Farmers in Beneficiary Communities of Kaduna State. It was assumed that if rural people are
provided with scientific ways of farming, it will lift them up from their poverty level thereby
increasing their output, hence their income and their livelihood.
One hundred and twenty structured interview questionnaires were randomly administered to
beneficiaries in the 28 settlements. The 28 settlements were divided into 4 clusters of 7 settlements
each. Another 28 check lists were also administered to the 28 village heads (opinion leaders) and

13. Nuhu Bamalli Polytechnic Multidisciplinary Journal 1 :( 1) 145-162 Barnabas et al., (2016)
one check list to an official of the MVP. The statistical tools used were descriptive statistics, Gini
coefficient and Lorenz curve.
The result shows that 98% of the beneficiaries were male headed households, 2% were female
headed households, 86% were married, 6.5% single, 5% divorced and 2.5% widowed. The married
beneficiaries were more because they had the responsibility to carter for their families.
The Gini coefficient value was 0.94 in 2011, that is to say 94% of the beneficiaries do not have
variability. That is to say only 6% have disparity in their income in 2011. The Gini coefficient
value for 2006 was 0.85 though 85% do not have income variation.
The mean income of the individual beneficiary before the MVP intervention was lower than their
income after the project intervention. It shows a mean income of an individual beneficiary to be
N240, 535.0 and N291, 017.0 for 2006 and 2011 respectively. The mean income was significant
at 10% probability level. Thus, the null hypothesis which states that there was no significant
difference between the livelihood of the beneficiaries before and after the Millennium Village
Project intervention was rejected and the alternative accepted.
CONCLUSION AND RECOMMENDATIONS
Conclusion
The beneficiaries reported that they got free drugs and farm inputs which greatly increased their
output and their income levels. In addition to this the study also revealed that there were more
contacts with extension workers which motivate the beneficiaries’ participation in the project.
Similarly, it was found out that the beneficiaries participated in the MVP activities to help them
reduce their poverty condition and hence feed their families. The provision of a health clinic and
school feeding programme encouraged them to send their wives and children to the clinic and
school respectively. Based on the above findings it can be said that the intensions of the MVP were
achieved in the study area. Poverty is a multi-faceted phenomena and addressing it requires both
internal and external efforts. The MVP could be said to be such external intervention that rural
dweller requires to move out of poverty.
Recommendations
Based on the findings from the study, the following recommendations are made:
MVP should incorporate leadership training in its activities; this will help in mobilization and
legitimization of the project for continuity and sustainability in the area.
There should be proper monitoring of staff by the MVP officials especially during the distribution
of any inputs and other related materials.
The project should be extended to other communities in the state. The federal, states and local
governments should intensify efforts in trying to reach more target areas with a view to realize the
set objective of the MVP by the year 2015.
Government needs to establish veterinary clinics in the area based on the prevalence of animal
diseases outbreak in the area.

14. Nuhu Bamalli Polytechnic Multidisciplinary Journal 1 :( 1) 145-162 Barnabas et al., (2016)
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