Page 1 of 9

Journal for Studies in Management and Planning

Available at http://edupediapublications.org/journals/index.php/JSMaP/

e-ISSN: 2395-0463

Volume 02 Issue 5

May 2016

Available online: http://edupediapublications.org/journals/index.php/JSMaP/ P a g e | 80

Poverty Incidence among Rural Households in Ikot Ondo

Community, Nigeria

*1Jacob, D. E., *2Udeagha, A. U. and 1Nelson, I. U.

1 Forestry and Natural Environmental Management Department, University of Uyo, Uyo, Akwa

Ibom State, Nigeria

2Department of Forestry Technology, Hussaini Adamu Federal Polytechnic, Kazaure, Jigawa State,

Nigeria

*Correspondence email: danieljacob@uniuyo.edu.ng; aumazi@yahoo.co.uk

ABSTRACT

This study evaluates the extent, profile,

incidence and socio- economic determinants

of poverty among rural households in Ikot

Ondo, Akwa Ibom State, Nigeria. Data was

collected through a detailed structured

household survey using 50 randomly

sampled households. Descriptive statistics,

Gini coefficient, Foster-Greer-Thorbecke

(FGT) poverty measurement and

econometric model were employed to

analyse the data collected. The findings

revealed that majority 66% of the

respondents were actually poor and were

living below the poverty line of 1$ a day. The

result of Gini coefficient (0.38) implies the

existence of an average level of income

inequality among the respondents. The result

of regression analysis depicts that age

(p<0.05), marital status (p<0.001),

household income (p<0.001); years of

residence (p<0.10) and diversification of

incomes (p<0.10) were the major

determinants of poverty among rural

households. At policy level it is therefore,

recommended that more investment and

development should focused on improving,

localising and building upon on the existing

livelihood strategies on ground with more

emphasises on improving vocational

trainings/education and agricultural

activities. This would serve as catalyst in

alleviating poverty and also enhance the

overall wellbeing of the rural households in

the study area.

Keyword: localising, livelihoods strategies,

agricultural activities, poverty, policy, Ikot

Ondo, Nigeria

Introduction

Poverty is a complex, multidimensional,

universalsocio - economic and political

problem (Igbalajobi et al., 2013; Anyanwu,

2013; Cheema and Sial 2012; Fraser and

Baiyegunhi, 2009). Among the regions

considered as being the poorest, the Sub- Saharan Africa (Nigeria inclusive) is identified

as one of them whose rural economies are

heavily depended on subsistence agriculture

and collection of forest products as their

primary source of income and food (Fraser

and Baiyegunhi, 2009; Apataet al., 2010;

Igbalajobi et al., 2013; Jacob et al., 2013;

Anyanwu, 2013) thus practically climate- sensitive based.

In Nigeria rural poverty is relatively high

(Abebayo, 2013; Apata et al.,2010; Fraser and

Baiyegunhi, 2009) and overwhelmingly a rural

problem; two out of every three Nigerian live

below the poverty line of $1 per day in income

(Fraser and Baiyegunhi, 2009; Anyanwu,

2013; Adebayo, 2013). The increasing

incidence of poverty, both within and among

locations, was in spite of various resources

and effort exerted on poverty (Okunmadewa et

al., 2005; Fraser and Baiyegunhi, 2009;

Page 2 of 9

Journal for Studies in Management and Planning

Available at http://edupediapublications.org/journals/index.php/JSMaP/

e-ISSN: 2395-0463

Volume 02 Issue 5

May 2016

Available online: http://edupediapublications.org/journals/index.php/JSMaP/ P a g e | 81

Cheema and Sail, 2012). Its growing incidence

and depth in the country (Okunmadewa et al.,

2005; Adebayo; 2013) is quite worrisome

considering the vast endowment of the country

in both human and physical resources (Fraser

and Baiyegunhi, 2009). Several studies

dealing with the identification and analysing

the extent of poverty in the country have been

carried out (Olofin et al., 2015; Asogwa et al.,

2012; Apata et al.,2010; Babatunde, 2008),

with none of them actually quantifying the

impacts of the various factors that influenced

poverty in the country. In some African

countries (Burkina Faso, Mauritania and

Kenya, among others) unlike Nigeria, there

have been econometrics studies on the

determinants of poverty in their respective

domain. The lack of adequate information

therefore makes is very difficult to effectively

setup and implement sustainable policy and

programmes that would facilitate poverty

reduction in Nigeria. This study is therefore

aimed at assessing poverty status and its

determinant among rural households in Ikot

Ondo community, Akwa Ibom State, Nigeria

with the aim of filling the knowledge gap and

apparently contributing to scientific

knowledge of the policy makers and relevant

stakeholders in order to ensure sustainable

development that would alleviate poverty in

the country.

METHODOLOGY

Study Area

Ikot Ondo Community lies between latitudes

5

0

00N and longitudes 50

15N and longitude

7

0

35E and 70

45E in Essien Udim, Local

government Area which has an area of about

50km2

(Ukpong et al., 2012). The community

forest is a lowland rainforest located in

Adiasim, EssienUdim Local Government area

in Akwa Ibom State in South-South, Nigeria.

The forest has a surface drainage with an

average annual rainfall of 2000mm-3000mm.

Temperatures are uniformly high throughout

the year with slight variation between 26oC

and 28oC. The topography is moderately plane

with a little or no ridge or valley. It has a

tropical climate, it is significant most months

of the year, and the short dry season has little

effect. However, most of the rural household

depend on the forest for their subsistence

agriculture, hunting and gathering of forest

based resource for their food and non-food

needs which tend to degrade the ecosystem

and threatened the existence of the forest

(Ukpong et al., 2013).

Figure 1: Map of Akwa Ibom State showing study area

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Data Collection

The study utilised both secondary and primary

data. Secondary data collection sources

included: official documents as well as

relevant literature and research reports specific

to the area of study and phenomenon under

investigation. Structured questionnaire was

used in the gathering of the primary data

using 50 randomly selected households out of

the 273 household in the study area (i.e.

18.32%) in other to ensure variation and

representativeness (Udeagha 2015; Heubach

2012; Angelsen et al., 2011a; 2011b; Rubin

and Babbie, 2008; Babbie, 2005) and was

also supplemented by other ethnographic and

participatory methods of data collection such

as; field observation , visual photography,

transact walk , In-Depth Interviews (IDIs) and

Focus Group Discussions (FGDs) with

relevant community stakeholders who have

ample knowledge of the subject matter. This

was done with the assistance of community

leaders and their council.

Analytical Techniques

The Foster-Greer-Thorbecke (FGT) model was used to measure poverty status among the rural

households. The FGT poverty index as described by is given by:

- - - (1)

Where: n = total number of households in population q = the number of poor households

z = the poverty line for the household yi = household income

α = poverty aversion parameter

[ ] = proportion of shortfall in income below the poverty line

The incidence of poverty or headcount index was calculated using equation 2 below where α = 0 in

FGT. This measures the proportion of the population that is poor or fall below the poverty line.

- - - - - (2)

Poverty depth or poverty gap index is the measure of the extent to which individuals fall below the

poverty line as a proportion of the poverty line. This was calculated using the formula where α = 1,

hence the expression becomes;

- - - - (3)

Poverty severity index is the measure of the squares of the poverty gap relative to the poverty line.

This was calculated using the formula where α = 2, hence the expression becomes;

2

- - - - - - - - - (4)

The poverty line was constructed to categorize the respondents into poor and non-poor groups using

the two-third mean per-capita income as the benchmark as described by Ruben and van den Berg

(2001), Yunez-Naude and Taylor (2001), Adewunmi et al. (2011) and Fonta and Ayuk (2013).

Households whose mean per-capita income fell below the poverty line where regarded as being poor,

while those whose per-capita income where above the benchmark were regarded as non-poor.

Per-capita income (PCI) = Income / Household size

Total Per-capita income (TPCI) = ∑PCI

Mean TPCI (MTPCI) = TPCI / Total number of households

Poverty line (PL) = 2/3 × MTPCI

The Gini coefficient for total income was used to compute the income inequality among the

households and expressed graphically as recommended by Cheong (1999). The equation is expressed

mathematically as;

- - - - - - - - - (5)

Where;