sources of income inequality and … of income inequality and poverty in rural and urban nigeria...

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SOURCES OF INCOME INEQUALITY AND POVERTY IN RURAL AND URBAN NIGERIA A.S. Oyekale, A.I. Adeoti and T.O. Ogunnupe Department of Agricultural Economics, University of Ibadan, Ibadan, Nigeria. ABSTRACT Income inequality is detrimental to economic growth and development. In Nigeria, several studies have shown that income inequality is increasing in the rural and urban areas, and this can be linked to the growing dimension of poverty. This study therefore attempts to estimate the level of income inequality using the data from National Integrated Households’ Survey collected by the Federal Office of Statistics (FOS) in 2003. The mean, standard deviation, and coefficient of variation will be used to describe the distribution of households’ incomes, while Gini-coefficient will be used to measure income inequality. Also, decomposition of income sources into agricultural, livestock, rental, transfer, and non-farm incomes will be done using the Coefficient of variation and Gini-coefficent. The socio-economic determinants of per capita income, which is a measure of welfare, will be derived through an Ordinary Least Square (OLS) regression. This approach will be used to decompose the effect of some socio-economic variables on inequality. The z-statistics and t-statistics will be used to test some stated hypotheses. 1. INTRODUCTION The pattern of income distribution has been a concern to economists for a long time (Clarke et al, 2003). Specifically, the 1990s witnessed resurgence in theoretical and empirical attention by economists to the distribution of income and wealth (Atkinson and Bourguignon, 2000). This is because high level of income inequality produces an unfavourable environment for economic growth and development. Previous studies have shown that income inequality has risen in many developing countries over the last two decades (Addison and Cornia, 2001; Cornia with Kiiski, 2001; Kanbur and Lustig, 1999). The widening dimension of poverty has aroused serious humanitarian concerns and fears

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Page 1: SOURCES OF INCOME INEQUALITY AND … OF INCOME INEQUALITY AND POVERTY IN RURAL AND URBAN NIGERIA A.S. Oyekale, A.I. Adeoti and T.O. Ogunnupe Department of Agricultural Economics, University

SOURCES OF INCOME INEQUALITY AND POVERTY IN RURAL AND URBAN NIGERIA

A.S. Oyekale, A.I. Adeoti and T.O. Ogunnupe Department of Agricultural Economics,

University of Ibadan, Ibadan, Nigeria.

ABSTRACT

Income inequality is detrimental to economic growth and development. In

Nigeria, several studies have shown that income inequality is increasing in the rural and

urban areas, and this can be linked to the growing dimension of poverty. This study

therefore attempts to estimate the level of income inequality using the data from National

Integrated Households’ Survey collected by the Federal Office of Statistics (FOS) in

2003. The mean, standard deviation, and coefficient of variation will be used to describe

the distribution of households’ incomes, while Gini-coefficient will be used to measure

income inequality. Also, decomposition of income sources into agricultural, livestock,

rental, transfer, and non-farm incomes will be done using the Coefficient of variation and

Gini-coefficent. The socio-economic determinants of per capita income, which is a

measure of welfare, will be derived through an Ordinary Least Square (OLS) regression.

This approach will be used to decompose the effect of some socio-economic variables on

inequality. The z-statistics and t-statistics will be used to test some stated hypotheses.

1. INTRODUCTION

The pattern of income distribution has been a concern to economists for a long

time (Clarke et al, 2003). Specifically, the 1990s witnessed resurgence in theoretical and

empirical attention by economists to the distribution of income and wealth (Atkinson and

Bourguignon, 2000). This is because high level of income inequality produces an

unfavourable environment for economic growth and development. Previous studies have

shown that income inequality has risen in many developing countries over the last two

decades (Addison and Cornia, 2001; Cornia with Kiiski, 2001; Kanbur and Lustig, 1999).

The widening dimension of poverty has aroused serious humanitarian concerns and fears

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of political instability. It has therefore become evident that in absence of strong foreign

markets, the domestic inter-sectoral linkages and policy environment required for rapid

economic growth cannot be provided by policies which result in further concentration of

national income in the hands of few proportion of the population (Aigbokhan, 1999;

Clarke et al, 2003).

Despite the commitments already shown by many developing countries towards

the achievement of the goal of reducing income inequality, efforts geared at achieving

this have been greatly hindered by insufficient knowledge of how to design appropriate

policies that would call for broad participation, the modality of their implementation

procedures and measurement of the overall impact on the economy (Matlon, 1979).

Many empirical studies have assessed the impact of some macro-economic policies on

economic development based on the level of income inequality during the periods of their

implementation. A common model proposed has explained this secular trend based on

inter-sectoral income differentials and changes in the incomes of the citizenry resulting

from the growth processes (Matlon, 1979; Ahluwalia, 1976; Fields, 1980; Yang, 1999).

In Nigeria, accompany the rapid economic growth that was had between 1965 and

1974 was a serious income disparity believed to have widened substantially (Matlon,

1979; Aigbokhan, 1997; Ipinnaiye, 2001). Despite the past policy interventions to

correct this abnormality, the problem of income inequality has increased poverty depth in

some urban and rural areas. During the Structural Adjustment Program (SAP), for

instance, Aigbokhan (1997, 1999) submitted that a quantitative analysis of the level of

income inequality before and after the implementation of the policy shows that income

inequality worsened.

2. PROBLEM STATEMENT

High level of income inequality exists in many nations of the Sub-Saharan Africa

(SSA). This can be better buttressed by the widening dimension of poverty, and general

economic problems in many of these nations. Thirlwall (1994) stated that low income

countries contain approximately 62% of the world’s population, and earn only 6% of the

world’s income, medium income countries contain 15% of the world’s population and

earn 17% of its income, while high income countries contain 25% of the world’s

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population and earn 77% of the income. This shows a great disparity between total

incomes and per capita income of the developed and developing countries.

In Nigeria, Adelman and Morris (1971) estimated a Gini coefficient of 0.51,

showing high level of income inequality. Aboyade (1974), using the 1966/67 household

sample survey of 1,635 households, covering wage earners, the self-employed and

farmers in the whole country except the eastern region that was going through civil war,

estimated the Gini Coefficient to be 0.58. Etukodo (1978) focused on whether income

inequality was higher in urban areas than in rural areas. Using data for the Federal Public

Service in Lagos and a sample of 400 farming households in Ika village of Cross Rivers

State, his results suggested that income inequality was lower in rural Ika than in urban

Lagos. More recently, Oyekale (1997), Adejare (1999), Odedele (2000), Ipinnaiye (2001)

and Adebayo (2002) have shown that income inequality exists in some rural and urban

areas in several parts of Nigeria.

A high level of income inequality exists between Nigerian rural and urban areas.

This is because urban dwellers usually earn more than rural dwellers due to their higher

literacy level. Higher incomes go to people who have invested time and money to acquire

skills (Udo-Aka, 1975). This differential between rural and urban incomes, most times,

accounts for the rural–urban migration. Most times, inhabitants of rural areas migrate to

the urban areas in search of the proverbial pot of gold or greener pastures because they

feel the urban areas hold more opportunities for them than the rural areas. This influx of

rural dwellers into the urban areas results in over-population and over-taxing of the

amenities available in the urban areas.

Also, most rural communities are agrarian as compared to urban communities

(which engage mostly in paid employment), thus they earn less than urban communities.

The problem then arises as to how high level of income inequality can be reduced.

Inequality in income has many social and economic implications. A high level of income

inequality results into discontent among the people, which may result into political unrest

and instability. It may also lead to increase in violence, corruption, and attitude of

helpless resignation to the caprice of nature and poverty. Thus, it is very pertinent to

study income inequality in order to reduce the dimension of poverty.

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Income inequality can be detrimental to economic growth and development of a

country. As part of macroeconomic objectives, governments always give equitable

distribution of income and wealth among the citizens a priority. This emphasizes the

importance of income inequality. Addison and Cornia (2001), Adams (1999), Adams and

He (1995) and Aboyade (1983) have proved in their various studies that income

inequality is closely related to poverty. Thus, a careful study of income inequality also

gives insight into the incidence of poverty.

3. THEORETICAL FRAMEWORK AND LITERATURE REVIEW

Inequality implies different things to different people. It could be conceptualized

as the dispersion of a distribution, whether one is considering income, consumption or

some other welfare indicator or attribute of a population. Conceptually distinct as they

may be, income inequality is often studied as part of broader analyses covering poverty

and welfare. Inequality is a broader concept than poverty in that it is defined over the

whole distribution, not only the censored distribution of individuals or households below

a certain poverty line (World Bank, 1999; Cowell, 1999).

Inequality can be measured in different ways. Since Atkinson (1970), most

questions about the measurement of inequality have been formulated using the explicit

logic of social choice theory: desirable properties are articulated and the indices or

methods are judged according to how well they conform to the properties. Debates go on

about the merits and disadvantages of various subsidiary properties, but there is broad

consensus on a core of axioms (Morduch and Sicular, 2002). Dalton (1920) and Pigou

(1912) proposed the Pigou-Dalton transfer principle which shows that inequality

increases as result of an income transfer from a poorer person to a richer person

(Atkinson, 1970, 1983, Cowell, 1985, Sen, 1973). Most measures in the literature,

including the Generalized Entropy class, the Atkinson class and the Gini coefficient,

satisfy this principle, with the main exception of the logarithmic variance and the

variance of logarithms (Cowell, 1995). Dalton (1920) proposed the population principle

of income inequality measurement which stated that inequality measures are invariant to

replications of the population. This implies that merging two identical distributions will

not alter the level of inequality. However, the income scale independence proposition

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requires that inequality measures are invariant to uniform proportional changes. This

shows that if each individual’s income changes by the same proportion (as it sometimes

happens when currency units are changed) then inequality should not change.

Furthermore, anonymity principle, sometimes referred to as ‘Symmetry’ - requires

that inequality measures are independent of any characteristic of individuals other than

their income (or the welfare indicator whose distribution is being measured). The

principle of decomposability noted that overall inequality is related consistently to

constituent parts of the distribution, such as population sub-groups. For example if

inequality is seen to rise amongst each sub-group of the population then we would expect

inequality overall to also increase.

Some measures, such as the Generalised Entropy class of measures, are easily

decomposed and into intuitively appealingly components of within-group inequality and

between-group inequality: Itotal = Iwithin + Ibetween. Other measures, such as the Atkinson set

of inequality measures, can be decomposed but the two components of within- and

between-group inequality do not sum to total inequality. The Gini coefficient is only

decomposable if the partitions are non-overlapping, that is the sub-groups of the

population do not overlap in the vector of incomes.

Kuznets (1955), based on long run time series data for three developed countries

(U.S., England, Germany) hypothesized a time path of inequality for nations undergoing

economic development with an increase in inequality in the early stages, followed by a

decrease in later stages. This has come to be known as the Kuznet U-shaped curve

hypothesis on relationship between inequality and development.

Kuznet (1963) observed that average income from non-agricultural sectors were

higher than those from agricultural activities and were associated with differences in

organization, technology and productivity. Intra-sectorally, income inequality was lower

within the agricultural than within the non-agricultural sector for most countries, although

the agricultural sector’s inequality was still higher for the under-developed than the

developed countries. He also observed that the degrees of income inequality seemed to

worsen with development, because of the rising relative importance of non-agricultural

activities. Milanovic (1998) noted that almost all socialist countries had low degrees of

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income inequality before their transition from planned economy to market economy.

Income inequality in socialist countries derives mainly from inequality in wages and not

from ownership of capital, which is largely in public hands.

Adam and He (1995) recently noted that the work of Kuznets (1955, 1963) on the

relationship that exists between development and income inequality has given further

inspirations to researchers in the drive towards accurately discovering the major

component sources of income inequality. A micro-survey of some households in Ibadan

by Oyekale (1997) revealed that Gini-coefficeint was 0.3716, while Adejare (1999)

estimated 0.57. World Bank (2003) shows that in 1996/97, Gini index for Nigeria was

0.506, while Ghana and Cameroon have 0.407 and 0.477 respectively. Using 1998 data,

World Bank (2003) also estimated Gini-indices of 0.613 and 0.526 for Central African

Republic and Zambia respectively. In rural Tanzania, Ferreira (1996) found that during

the period of structural adjustment, there was a reduction in poverty but income

inequality increased between 1983 and 1991. From all these studies, it can be deduced

that income inequality is high in many African nations, especially Nigeria.

Decomposition of income inequality is desirable for both arithmetic and analytic

reasons (World Bank, 1999). Economists and policy analysts may wish to assess the

contribution to overall inequality within and between different sub-groups of the

population, for example within and between workers in agricultural and industrial

sectors, or urban and rural sectors. Decompositions of inequality measures can shed light

on both its structure and dynamics. Inequality decomposition is a standard technique for

examining the contribution to inequality of particular characteristics and can be used to

assess income recipient characteristics and income package influences. These analyses

were pioneered by Bourguignon (1979), Cowell (1980), and Shorrocks (1982a; 1984).

Ipinnaiye (2001) found that decomposition analysis of income shows that non-

farm income contributes the most to overall income inequality in both the peri-urban and

urban areas of Ibadan. Also, income inequality was higher in peri-urban areas than urban

areas in 2000. Adebayo (2002) found that in the rural areas in Ibadan metropolis,

agricultural income contributes most to the overall income inequality accounting for 91%

while rental income makes the least contribution to overall rural income inequality

accounting for just 0.17%. In the urban areas, non-farm income makes the largest

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contribution to overall income inequality accounting for 88% while transfer income

reduces urban overall income inequality by 0.13%.

Piesse et al (1998) used a Gini decomposition to analyse the effects of crop,

animal and non-farm income on the distribution of total income in the communal lands in

Zimbabwe. Results show that non-farm income decreases inequality in Chiweshe, which

is near Harare. Particularly, a substantial part of reduction in equality arises from greater

non-farm incomes at the bottom of the scale, so poverty is reduced by access to

alternative income sources. However, in the more remote and traditional region of

Gokwe, non-farm income increases inequality, accruing particularly to the relatively well

off rather than the poor. Thus, it was concluded that the opportunities offered by the

development of markets and non-farm opportunities appear to be important to poverty

reduction.

Adams (1999) used household-level data from a nationally representative survey

to analyze the impact of nonfarm income on income inequality in rural Egypt. The

decomposion was done using total rural income among five sources of income, which

were nonfarm, agricultural, livestock, rental and transfer. The analysis shows that while

nonfarm income represents the most important inequality-decreasing source of income,

agricultural income represents the most important inequality-increasing source of income.

Jacobs (2000) found that in Japan, Taiwan and South Korea, total income

inequality accounted for by differences between age groups is very low (less or equal to

5%). Inequality was much more prevalent between individuals of the same age category

than between the means of different age groups. In other words, age does not explain

much of the observed income inequality in any of the three countries.

Bouillon et al (2001) used a simulation empirical framework to identify the

contribution of microeconomic factors to increasing income inequality in Mexico in 1984

and 1994. Having specified different regression equations for the determinants of per

capita income in 1984 and 1994, they proceeded to simulate the impact of changes in

observable and unobservable characteristics. The micro-simulation method decomposes

the observed changes in the distribution of income into “return effect”, “population

effect” and the “effect of unobservables”. Results showed that changes in returns to

household characteristics, in particular changes to education are responsible for about 50

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percent increase in Gini-coefficients. The deteriorating conditions in rural areas relative

to the urban areas and of the southern region relative to other regions account for another

25 percent increase in the Gini.

Morduch and Sicular (2002) introduced a new integrated regression-based

approach for decomposing inequality indices with household-level data, and examined

the strengths and weaknesses of inequality decompositions by income source in light of

the way that they are commonly interpreted. The approach uses estimated income flows

from variables in linear income equations to decompose aggregate inequality indices. The

integrated approach provides an efficient and flexible way to quantify the roles of

variables like education, age, infrastructure, and social status in a multivariate context.

These tools are applied to a new data set with rich information on incomes in Zouping

County in Shandong Province, China. The evidence from China illustrates the sharp

differences that can result when using decomposition methods with varying properties,

and it demonstrates advantages of the proposed, integrated method. The empirical results

show the importance that spatial segmentations play in increasing inequality: village of

residence strongly drives inequality in the sample. This force is counter-balanced in part

by the relatively equitable distribution of human capital, especially demographic

variables. Contrary to other recent findings, affiliation with the Communist Party and

measures of social status have a very limited role in explaining inequality.

Alayande (2003) decomposed income inequality and poverty in Nigeria with the

regression-based decomposition approach developed by Morduch and Sicular (2002)

using the 1996 data collected by the Federal Office of Statistics (FOS). The results

showed that primary and post-secondary educational attainments are important in

reducing income inequality in Nigeria, while the number of unemployed in the

households contributed positively to income inequality.

Elbers et al (2003) estimated income inequality for Ecuador, Mozambique and

Madagascar. Based on a statistical procedure that combines household survey data with

population census data, their analyses showed that the share of within-community

inequality in overall inequality is high. Specifically, computed Gini-coefficients were

between 0.320 – 0.518 and 0.320 – 0.440 in Madagascar and Mozambique respectively.

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4. JUSTIFICATION FOR THE STUDY

Several studies in Nigeria have decomposed income inequality by economic

sector (urban versus rural), income source (income from labour versus income from

capital versus land) and family characteristics (including educational and occupational

attributes of workers). Most of these studies were conducted at the Local Government

level, and the studies are useful because they help to identify the structure of income

inequality within a given society. However, their application for policy formulation at the

national level is limited due to small scope. This study seeks to use the most current

national data, and will add to the already existing body of knowledge by decomposing the

sources of income inequality using five income sources. The knowledge of the various

sources of income inequality will help policy makers to formulate policies that will

ensure reduction in the level of income inequality in the country. Knowing the sources of

incomes that increase overall income inequality will also make it possible for

developmental efforts to be concentrated on income sources that reduce income

inequality to enhance the welfare of the least privileged in every community in the

nation. The knowledge of the sources of income inequality will therefore help in reducing

poverty, because several studies have established the fact that poverty is invariably

related to income inequality. Also the study attempts to go a step further by using the

regression-based decomposition of income inequality recently developed to decompose

inequality in welfare based on the socio-economic characteristics of the households. This

implies that the findings of the study will not only focus on the occupational groupings of

the households for policy implementation, but will equally address the effect of some

socio-economic factors. This, no doubt will assist Nigerian policy makers to select the

best option for ensuring rapid economic growth and development amidst diverse

competing options.

5. OBJECTIVES OF THE STUDY

The general objective of the study is to determine the sources of income inequality

among some rural and urban households in Nigeria. The specific objectives are:

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i. To determine the level of income inequality in the rural and urban areas;

ii. To determine the contribution of each income source to overall income inequality;

and

iii. To decompose income inequality based on some socio-economic characteristics

of the rural and urban households.

iv. To determine the effect of some socio-economic characteristics of households on

per capita income (measure of welfare).

6. RESEARCH HYPOTHESES

The following null hypotheses will be tested for acceptance or rejection in the

study:

Ho1: There is no significant difference between the income received from different

sources in the urban and rural areas.

Ho2: None of the socio-economic characteristics has significant influence on the per

capita income of the households in the rural and urban areas..

Ho3: There is no significant difference between inequality in welfare and socio-

economic classes of households in the rural and urban areas.

7. METHODOLOGY

Sampling Procedures

The data for the study will be collected from the Federal Office of Statistics

(FOS). The data are based on National Integrated Survey of Households (NISH) that was

carried out in all the states of the nation in 2003. The sample design that was used is two

stage stratified sampling with the 1st stage involving clusters of housing units called

Enumeration Area (EA), and the 2nd stage involves the housing unit. The sample size is

determined from 120 EAs selected in each of the 36 states of the nation and Abuja which

is the Federal Capital Territory (FCT). Out of these, 5 housing units were selected

randomly from each of the EAs. A total of 600 households will be randomly chosen in

each of the states, implying that 22,200 households were selected in all (FOS, 2003).

However, the data to be used in this study will be drawn from 6 of the states to be

randomly selected from the 6 geo-political zones in Nigeria- 1 states per zone. The zones

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are south-south, south west, south east, north central, north east and north-west. This

shows that the number of respondents to be included in this analysis will be 3,600.

The concept of income used in the study reckons with income earned both in cash

and in kind. Therefore, money values were allocated to receipts of income in kind and

household consumption of crops and livestock produced based on prevailing market

prices. Values were also computed for houses occupied by their owners. Recognition was

made of whether incomes recorded were incomes before or after taxation. Following

Adams and He (1995), the study identified the following sources of income:

• Non-farm income: includes income realized from non-farm labours, government

and private sector employment (full or part time), and profits from non-farm

enterprises.

• Agricultural income: includes net income from all crop production with imputed

values from home production and agricultural labours.

• Transfer income: includes income from relatives within and outside the country,

government pension and other gifts received.

• Livestock income: includes net income from cattle, poultry, sheep, goat and pigs

etc.

• Rental income: includes net income received from ownership of assets.

Measurement of Income Inequality

In order to achieve objective 1, the following descriptive statistics will be used to

analyze the pattern of income distribution: the standard deviation, kurtosis, skewness,

coefficient of variation, and the mean. Income inequality will be measured using the

Gini-Coefficient. Following Morduch and Sicular (2002), where incomes are ordered so

that Y1 ≤ Y2 ≤ Y3 ≤…… ≤Yn Gini-coefficient is computed as

I gini (Y) = i

n

i

Ynin ∑

=⎟⎠⎞

⎜⎝⎛ +−

12 2

12µ

……. 1

Where n is the number of observation, µ is the mean of the distribution, Yi is the income

of ith household. This measure of income inequality conforms with the Pigou-Dalton

transfer principle, income scale independence, principle of population, and anonymity or

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symmetry but fails the decomposability axiom if the sub-vectors of income overlap.

However, several authors have shown that Gini-coefficient can be decomposed

successfully.

Decomposition Based on Coefficient of Variation

In order to fulfill objective two, the sources of income inequality would be

decomposed based on the coefficient of variation and Gini Coefficient. Although the two

approaches give similar results, we are specifically interested in knowing what the

outcomes would be for this data set. Following Shorrocks (1982b) suppose total income

(Y) consists of income from k sources. The variances of each of the sources of income,

σi2, and the covariances between sources of income σij

2 can be expressed as equal to

variance of total income.

σ2 = ∑σi2 + ∑σij ……………………2

The contribution of the ith source of income to households’ total income variance

comprises of the jth income variance and part of the covariances allocated to the ith

source. Also, the natural decomposition of the variances assigned to the ith source exactly

one-half of all covariances involving the ith source of income. This can be expressed as:

σ2 = ∑σiy …………………….3

Furthermore, the decomposition corresponding to the coefficient of variation can be

further expressed as:

∑wici = 1; ……………………….4 wi = µi/µ; ………………………5 ci = ρ σi/µI ….…………………………6 σ/µ

where: wici = factor inequality weight of the ith source in overall inequality

µI = mean of income from ith source

µ = mean of total income from all sources

ci = relative concentration coefficient of ith source in overall inequality

ρ = correlation coefficient between the ith source and total income

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Decomposition Based On Gini-Coefficient

Following Pyatt et al (1980), the Gini-coefficient can be decomposed as follows:

G = 2 Cov (Y,,r) …………………….7 nµ

where n is the number of observations, Y is the series of total income and r is the series of

corresponding ranks.

The Gini coefficient of the ith source of income, Gi can be expressed as Gi = 2 Cov (Yi,ri) ……………………8 nµi

where Yi and ri refer to the series of income from the ith source and corresponding ranks

respectively. Since total income is the sum of source incomes, the covariance between

the total income and its rank can be written as the sum of covariances between each

source income and rank of total income. The total income Gini can then be expressed as

a function of the source Ginis.

..........................................................111

1 ∑ == GRGµµ 9

Where Ri is the correlation ratio expressed as:

( )( ) .......................................................................

,,

11 rY

rYCovR = 10

where cov (Y, r) is the covariance of total income and corresponding rank respectively

and covi ( )irY ,1 the covariance of the ith source of income and corresponding rank.

The decomposition of Gini coefficient can be further expressed as:

∑ = .................................111gw 11

..................................11 µ

µ=w 12

................................111 G

GRg = 13

Where wigi is the factor income inequality weight of the ith source in overall

income inequality, wi is the source income weight and gi is the relative concentration

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coefficient of the ith source in overall inequality. An income source increases overall

income inequality when gi is greater than one and it decrease overall income inequality

when gi is less than one.

Regression-Based Decomposition

In order to fulfill objective three and four, the regression based decomposition

approach developed by Morduch and Sicular (2002) will be used. The decomposition is

done as follows:

Suppose an income equation is defined as:

Y=Xβ + ε 14

Where Y is the per capita income (N) and X is an n x M matrix of independent variables

with the first column given by the n-vector e = (1,1,….1),

More specifically, we propose the following variable specifications:

X1 = age of house head

X2 = age of house head square

X3 = Year of education of house head

X4 = Number of household members with primary education

X5 = Number of household members with secondary education

X6 = Number of household members with tertiary education

X7 = Household dependency ratio

X8 = Land owned (ha)

X9 = Migrant status Dummy (migrants = 1; 0 otherwise)

X10= Total number of hours household members worked per week

X11=Crop diversification index measured by the Herfindal Index which is

100*

2

1

1

∑∑=

=⎟⎟⎟⎟

⎜⎜⎜⎜

⎛n

in

ii

i

C

C with Ci being the area of land planted to ith crop.

X12 = Government job dummy (1 for government employment, 0 otherwise)

X13 = Farming job dummy ( 1 for farmers, 0 otherwise)

X14 = Trading job dummy (1 for traders, 0 otherwise).

X15 = Location dummy (urban 1, 0 otherwise)

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X16 = Number of people unemployed in the family

X17 = Amount of credit obtained (N)

X18 = Secondary occupation dummy (1 for Yes, 0 otherwise)

β is an M-vector of regression coefficients, and ε is an n-vector of residuals. The M

coefficients can be estimated using appropriate econometric techniques with specification

corrections as required. Predictions of per capita income ^^βXY = are formed using

information from the entire data set. However, a major limitation is that the influence of a

variable that is constant for all the observations cannot be estimated.

Since the econometric results yield estimates of the income flows attributed to

household variables, they allow us to decompose inequality by factor income- that is to

apportion inequality to the components of income, where the sum of these components

equals total income, ∑=

=k

k

kii YY

1

. In this case, the analogues are themm

XY^^β= , the income

contributed by the socio-economic variables as given in the estimated regression equation

(plus the regression residual):

∑+

=

=1

1

^M

M

Mi YY for all i, where

mim

m

XY^^β= for m = 1,……,M

^^

im

iY ε= for m = M+1

The income flow will then be used to directly calculate decomposition components for all

regression variables. The shares take the form:

⎟⎟⎟⎟

⎜⎜⎜⎜

=∑=

)(

)(),( 1

^

YI

XYaYXs

n

i

miim

m β for m = 1, ……….M 15

The standard errors can be computed since the decomposition in equation 15 is linear in

the estimated parameters. The standard error (.) can therefore be obtained from

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⎟⎟⎟⎟

⎜⎜⎜⎜

=∑=

)(

)()()),(( 1

^

YI

XYaYXs

n

i

miim

m β …………….. 16

Under the assumption of homoscedastic error, var ε = ε2 for all i, and

2/1

1

2

2 )()()),((

⎟⎟

⎜⎜

⎛⎟⎟⎠

⎞⎜⎜⎝

⎛= ∑

=

n

i

i

YIYaYs εε 17

The standard error provides confidence intervals for the estimated contributions to mean

values of the aggregate inequality indices, analogous to the interpretation of standard

errors in OLS regression analysis.

For application, inequality indices that can be written as a weighted sum of incomes was

then considered.

i

n

ii YaI ∑

=

=1

)()( YY 18

Many common indices can be written in this way and they include the variance and

squared coefficient of variation, the Theil indices and the Gini-coefficient. The

proportional contribution of source k to overall inequality is simply expressed as:

)(

)(),( 1

Y

YYY

I

Yas

n

i

kii

k∑== 19

and the sum of the k proportional contributions will equal one by construction. Given the

condition for deriving equation 1, the Gini decomposition can be decomposed as the

proportional share of inequality for source k and expressed as:

=

=

⎟⎠⎞

⎜⎝⎛ +−

⎟⎠⎞

⎜⎝⎛ +−

= n

ii

n

i

ki

kGini

Yni

YniS

1

1

21

21

)(Y 20

With respect to coefficient of variation, the decomposition is stated as:

∑=

=−==n

iiVarCV

YYYn

YIYI1

2122 )var()(1)()(

µµ

µµ 21

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)(),(

)()(

)()(YVar

YYCovYYYY

YsYsk

i ii

ik

iikVar

kCV =

−==∑∑

µµ

22

Finally, for Theil indices, the property is not violated. The decomposition is stated as

follows for Theil-T index:

,ln1)(1

⎟⎟⎠

⎞⎜⎜⎝

⎛= ∑

= µµi

n

i

iTT

YYn

YI

=

=

⎟⎟⎠

⎞⎜⎜⎝

⎟⎟⎠

⎞⎜⎜⎝

=n

i

ii

n

i

iki

kTT YY

YYYS

1

1

ln

ln)(

µ

µ 23

⎟⎟⎠

⎞⎜⎜⎝

⎛= ∑

= i

n

i i

ki

TL YYY

nYI µln1)(

1

⎟⎟⎠

⎞⎜⎜⎝

⎛= ∑

= i

n

i i

kik

TL YYYYS µln)(

1

24

8. EXPECTED OUTPUT AND DISSEMINATION

The findings of this study will go a long way in addressing the protracted poverty

problem in Nigeria. This is because identification of income source that is inequality

increasing will assist in formulating the right policies to address it. Policy makers will

therefore find the study very relevant for drawing policy issues in line with the challenges

of ensuring improved living condition for all Nigerians in this democratic dispensation.

The findings will be included as part of the Policy Briefs to be submitted to the Federal

Government of Nigeria as research findings and inputs from our Department to national

economic growth and development. Findings of the study will also be discussed in related

conferences and seminars both at the national and international levels. The study will add

to existing literature on the issue of income distribution in Nigeria and the papers to be

published there from will serve as basis for promoting the researchers and quick

references for students being taught by us and others in related fields. Books and other

materials acquired through the study used will help the researcher in teaching and in

conducting further research on issues related to Welfare Economics.

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9. PRIOR TRAINING AND EXPERIENCE OF RESEARCHERS

Mr. Oyekale (Team Leader)

I am one of the academic staff in the Department of Agricultural Economics,

University of Ibadan, Ibadan, Nigeria. I obtained B. Sc. (First Class Hons.) and M. Sc.

Degrees in Agricultural Economics from the University of Ibadan in 1994 and 1997

respectively. I have been lecturing since September 2000 and my PhD program

simultaneously commenced in 2000/2001 session. I have been involved in teaching

courses like Econometrics, Principles of Macro Economics, Agribusiness Management,

Statistics and Research Methods and Introduction to Computer in Agriculture at the

undergraduate level. I have completed the supervision of 14 B. Sc. students on different

topics like child labour, deforestation, HIV and agricultural production, income

inequality, poverty, land use and agricultural intensification, inflation and agricultural

growth, consumer analysis, marketing of agricultural produce etc. Currently, I am

supervising 7 undergraduate students in our Department. My PhD program for which I

got a grant award from the African Economic Research Consortium, Nairobi, Kenya, has

significantly advanced from the post data seminar to registration of thesis’ title. The oral

examination has been scheduled for mid-March 2004. Since my appointment in 2000, I

have published 15 of my research papers in reputable Journal in Nigeria and outside the

country. It is equally worthy to note that I have written and published a text book on

“Introduction to Computer in Agriculture”.

Moreover, I participated in the field surveys of a study commissioned by the

World Bank on “Institution Strengthening for the Second Phase of Fadama Project”

commissioned to BDO – OFO in 2001. Also, I was involved in another study on

“Developing Indicators for Accessing the Performance of Fadama Project” by the

Department of Agricultural Economics in 2001/2002. I am currently part of the 7-men

team handling a study on “Waste to Wealth Project” of the University of Ibadan. I have

also attended conferences and workshops in Nigeria. However, many of my papers have

been accepted for international conferences, and in 2003, I got a Rockefeller Foundation

Grant to attend the International Association of Agricultural Economists conference that

was held in South Africa. With these experiences (and those of my colleague team

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members), I have no doubt that we are competent to successfully conduct this study if

sponsored by PEP. REFERENCES

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International Edition. Adams, R. H. (Jr.) and J. J. He (1995). Sources of Income Inequality and Poverty in

Rural Pakistan. Research Report 102, International Food Policy Research Institute, Washington D. C.

Adams, R.H/ (Jr.) (1999). Nonfarm Income, Inequality and Land in Rural Egypt.

PRMPO/MNSED, Unpublished Report for Comment, World Bank, Washington DC.

Adebayo, O. (2002). Sources and Measurement of Income Inequality Among Some Rural

and Urban Households in Ibadan Metropolis. B.Sc. Project, Dept. of Agric. Econ, University of Ibadan, Ibadan.

Adejare, A. A. (1999). The Impact of Soyabean Consumption on Food Sufficiency in

Ibadan Metropolis. Unpublished M. Sc. Theses in Department of Agricultural Economics, University of Ibadan, Ibadan, Nigeria.

Adelman, I. and C. T. Morris (1991). The Anatomy of Income Distribution in Developing

Nations. Mimeo (USAID) Washington D. C. Addison T. and G.A. Cornia (2001). Income Distribution Policies for Faster Poverty

Reduction. WIDER Discussion Paper No. 2001/93, World Institute for Development Economic Research.

Ahluwalia, M. S. (1976). “Income Distribution and Development Some Stylised Facts.”

American Econ (May) 128 – 135. Aigbokhan, B. E. (1997). Poverty Alleviation in Nigeria: Some Macroeconomic Issues”

NES Annual Conference Proceedings pp. 181 – 209. Aigbokhan, B. E. (1999). The Impact of Adjustment Policies and Income Distribution in

Nigeria: An Empirical Study Research Report, No. 5. Development Policy Centre (DPC), Ibadan, Nigeria.

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20

Alayande, B. (2003). Decomposition of Inequality Reconsidered: Some Evidence From

Nigeria. Paper submitted to the UNU-WIDER for the conference on Inequality, Poverty and Human Well Being in Helsinki, Finland Between 29th and 31st of May 2003.

Atkinson, A.B. and F. Bourguignon (2000) ‘Introduction: Income Distribution and

Economics’, in A.B. Atkinson and F. Bourguignon (eds) Handbook of Income Distribution Vol.1, North Holland: Amsterdam.

Bouillon, C.P., A. Legovini and N. Lustig (2001). Rising Inequality in Mexico: Household Characteristic and Regional Effects. Part of Research Report on “The Microeconomic Of Income Distribution Dynamics in East Asia and Latin America” JEL Classification D1.

Bourguignon, F.,1979, "Decomposable Income Inequality Measures", Econometrica, 47:

901-20. Bronfrenbrenner, M. (1971). Income Distribution Theory, Aldine: Chicago. Clark, J. B. (1899). The Distribution of Wealth Macmillan: London. Clarke, G., L. Colin, X.H. Zou (2003): Finance and Income Inequality: Test of

Alternative Theories. World Bank Policy Research Working Paper 2984, Washington D.C.: World Bank.

Cline, W. R. (1972). Potential Effects of Income Redistribution on Economic Growth:

Latin American Cases. Praeger Publisher, New York, Washington, London. Cornia G.A. with S. Kiiski (2001). Trend in Income Distribution in the Post World War

II Periods: Evidence and Interpretation. WIDER Discussion Paper No. 89, UNU/WIDER: Helsinki.

Cowell, F.A., 1980, "On the Structure of Additive Inequality Measures", Review of

Economic Studies, 47: 521-31. Cowell, F.A., 1999, "Measurement of Inequality" in Atkinson, A.B. and F. Bourguignon

(eds) Handbook of Income Distribution, North Holland, Amsterdam. Elbers, C., P. Lanjouw, J. Mistiaen, B.Özler and K. Simler (2003). Are Neighbours

Equal? Estimating Local Inequality in Three Developing Countries WIDER Discussion Paper No. 2003/52, World Institute for Development Economic Research (WIDER)

Etukodo, A. (1978): Household Income Distribution, Mimeograph Department of Economics.

Fields, G. S. (1980). Poverty, Inequality and Development Cambridge: (CUP).

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21

Federal Office of Statistics (FOS) (2003). Nigeria Living Standard Survey: Interviewers Instruction Manual FOS, Abuja, Nigeria.

Ferreira L. (1996). Poverty and Inequality During Structural Adjustment in Rural

Tanzania. World Bank Policy Research Working Paper 1641. Washington DC. World Bank

Ipinnaiye, A. O. (2001). A Decomposition Analysis of the Sources of Income Inequality

in Ibadan Metropolis Unpublished B. Sc. Project Dept. of Agric. Economics, U. I. Jacobs, D. (2000) Low inequality with low redistribution? An analysis of income

distribution in Japan, South Korea and Taiwan compared to Britain CASEpaper 33 Centre for Analysis of Social Exclusion. London School of Economics Houghton Street London.

Kanbur, R. and N. Lustig (1999). Why Is Inequality Back on the Agenda. Paper Prepared

for the Annual Bank Conference on Development Economics, World Bank Washington DC. April 28-30, 1999.

Kuznets, S. (1955). “Economic Growth and Income Inequality”. American Economic

Review 45 (March) 1 – 28. Kuznets, S. (1963). Quantitative aspects of the economic growth of nations: Distribution

of Income by Size. Economic Development and Cultural Change 11 (October) 1 – 80.

Matlon, P. (1979). Income Distribution Among Farmers in Northern Nigeria: Empirical

Result and Policy Implications. African Rural Economy paper No. 18 East Lansing, Mich, U.S.A.: Michigan State University.

Milanovic, B. (1998): Income, Inequality and Poverty During the Transition from

Planned Economy to Market Economy: World Bank Regional and Sectoral Studies. Washington DC. World Bank

Morduch, J. and T. Sicular (2002). Rethinkin Inequality Decomposition with Evidence

from Rural China. The Economic Journal 112:93-106. Odedele, A.E. (2000): A Comparative Analysis of the Poverty Level Between Salary

earners and the Self-Employed People in Agbowo Area of Ibadan North Local Government Council, Unpublished M.Sc. (Agric. Econs.) Project Report.

Oyekale, A. S. (1997). Households Demand for Groundnut Cake in Ibadan North Local

Government. Oyo State M. Sc. Project University of Ibadan, Ibadan.

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Piesse, J., J. Simister and C. Thirtle (1998).Modernisation, Multiple Income Sources and Equity: A Gini Decomposition for the Communal Lands in Zimbabwe JEL classification: D31

Pyatt, G.C., C. Chen, and J. Fei (1980). The Distribution of Income by Factor

Components. Quarterly Journal of Economics 95 (November: 451-473. Shorrocks, A.F. (1982a), "The Impact of Income Components on the Distribution of

Family Incomes", Quarterly Journal of Economics, 98: 311-26. Shorrocks, A.F. (1982b): Inequality Decomposition by Factor Components.

Econometrica. Shorrocks, A.F. (1984). "Inequality Decomposition by Population Subgroup",

Econometrica, 52: 1369-85. Solow, R. (1974). Capital Theory and Rates of Return. Rand McNally: Chicago. Taubman, P. J. (1975). Sources of Inequality in Earnings North-Holland, American

Elsevier. Thirlwall, A.P. (1994): Growth and Development with Special Reference to Developing

Economics, Macmillan Publisher. Udo-Aka, U. (1975): “Some Issues in Personal Income Distribution in Nigeria”. Paper

presented at the 1975 Annual Conference of the Nigerian Economic Society. Yang, T. D. (1999). “Urban Biased Policies and Rising Income Inequality in China”.

Agricultural Economics Association Papers and Proceedings. Vol. 89, No. 2: 307 – 310.

World Bank (2003). 2002 Development Indicators Washington D.C.: World Bank pages

74-75. World Bank (1999). Inequality Measurement and Decomposition, World Bank

PovertyNet

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WORK PLAN

Activity Time scheduled Literature search 2 month Data collection 3 months Data analysis 2 month Writing of draft report 3 months Correction and writing of final report 2 months Total 12 months RESEARCH BUDGET Activity US ($) Data collection expenses 2500 Salary for 1 research assistant @ $250 per month for 12 months 3000 Research related transportation expenses 1500 Postage and telecommunication 1000 Computer set and software for data analysis 3000 Stationary and miscellaneous expenses 1500 Journals and books 2000 Total cost 14500

Researchers’ institutions contribution to salary during the period of research $10, 000

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CURRICULUM VITAE Full Name: Abayomi Samuel Oyekale Nationality: Nigerian State of Origin: Osun Home Town: Ipetumodu Sex: Male

Marital Status: Married Date of Birth: 9th December 1969 Postal Address: Dept of Agricultural Economics,

University of Ibadan, Ibadan, Nigeria.

Contact Address: Dept. of Agricultural Economics, University of Ibadan, Ibadan, Nigeria.

E-Mail Addresses: [email protected] ACADEMIC QUALIFICATIONS:

Date Institution/College Qualification/Result

1995-1997 University of Ibadan, Ibadan,

M.Sc. Agric. Econs. (GPA 69.9%)

1988-1994 University of Ibadan, Ibadan,

B.Sc. Agric. Econs. (First Class Honours)

1995 Centre for Research and Development, Ondo state University, Ado-Ekiti.

Cert. in Computer: Ms-Dos, WP, Dbase, Lotus 123, Word, and Excel

1981-1987

Origbo Community High Schl., Ipetumodu, Osun State.

8 O-Level Credits With English and Mathematics

EMPLOYMENT HISTORY 1. Employer: Center for Research and Development, (OSUA)

Position: Asst Senior Accountant Duration: May 1994 and April 1995 Responsibilities: Preparation of Journal and payment vouchers, posting of

different accounts into cashbook, preparation of the over-all account at the end

of the year, preparation of the monthly pay roll and auditing of the company’s

stock register.

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25

2. Employer: B -Y Consults, ANCE Building, Jericho, Ibadan Position: Research Assistant

Duration: Jan. 1999 to July Responsibilities: Research Survey, Data Collation, Data Analysis, Report writing

and research paper writing, literature search, office administration. 3. Employer: Cocoa Research Institute of Nigeria (CRIN)

Position: Research Officer I Duration: August - October 2000. Responsibilities: Research survey, data collation, data analysis, report writing,

research paper writing, paper presentation, literature search, office administration.

4. Employer: University of Ibadan, Ibadan.

Position: Assistant Lecturer Duration: November 2000 to date.

Responsibilities :

• 2000/2001 Session: Taught Agribusiness Management (AGE 513) and Principles of Macroeconomics (AGE 521). Supervised 7 undergraduate students on various project topics. Member of Undergraduate committee.

• 2001/2002 Session: Taught Statistics and Research Methods (AGE 511), Principles of Macroeconomics (AGE 521) and Computer in Agriculture (AGE 201). Supervised 7 undergraduate students on various project topics. Member of Undergraduate committee.

• 2002/2003 Session: Teaching Computer in Agriculture (AGE 201), Econometrics (AGE 516) and Natural Resource Economics (APA 716). Supervising 7 undergraduate students.

DEGREE PROJECT WORKS Oyekale, A. S. (1993): Economic Determinants of Households' Consumption of Gari in

Ife North Local Government Area of Osun State B. Sc. Project in the Department of Agricultural Economics, University of Ibadan, Ibadan, Nigeria.

Oyekale, A.S. (1997): Households' Demand for Groundnut Cake in Ibadan North Local

Government Area of Oyo State. M. Sc. Project in the Department of Agricultural Economics, University of Ibadan, Ibadan, Nigeria.

Oyekale, A.S. (2004). Land Use Dynamics and Sustainable Agricultural Production in

Nigeria. Undefended PhD Thesis in the Department of Agricultural Economics, University of Ibadan, Ibadan.

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PUBLICATIONS Books or chapters in books already published

1. Oyekale, A. S. (2001): “An Overview of the Problem of Land Degradation and

Global Food Security”. In NES (editor) Natural Resource Use, The Environment and Sustainable Development Selected papers Presented at the 2001 Annual Conference, Chapter 16 (pp 295-305), The Nigerian Economic Society, Ibadan.

2. Yusuf, S.A. A.S. Oyekale and A.O. Uwagboe (2003). Benefit Incidence Analysis

of Government Expenditure on Primary Health Care Services in Ibadan North Local Government Oyo State. Human Resource Development in Africa Selected Papers for the 2002 Annual, The Nigerian Economic Society. NES, Chapter 16 (pp 595-610) Ibadan.

3. Awoyemi T.T. and A.S. Oyekale (2003). The Role of Education in Non-Farm

Work Decisions in Rural Nigeria. Human Resource Development in Africa Selected Papers for the 2002 Annual Conference. The Nigerian Economic Society. NES, Chapter 16 (pp 481-497) Ibadan.

4. Oyekale A.S. and B.T. Omonona (2003 in press). Introduction to Computer in

Agriculture. Published by Distance Learning Program, University of Ibadan, Ibadan.

5. Oyekale, A.S. and T.O. Ogunnupe (2003). Continuous Cropping and Efficiency

of Food Crop Farmers in Delta State, Nigeria. In: O. Mertz, R. Wadley and A.E. Christensen (Eds.) Local Land use in A Globalizing World: Shaping Sustainable Social and Natural Environment Proceedings of the International Conference August 21-23 Institute of Geography, University of Copenhagen. Pp341-358.

(ii) Paper Published in Learned Journals 6. Oyekale, A. S. (2000): “An Application of Almost Ideal Demand Systems

(AIDS) to Food Demand in Nigeria” Nigerian Agricultural Development Studies. 1 (2):43-52.

7. Oyekale, A.S. (2001): Towards the development of workable technological

packages for sustainable and regenerative agriculture in Nigeria. Journal of Sustainable Tropical Agricultural Research. 2:116-121

8. Oyekale, A.S. (2001): Crop losses due to pests in tropical agriculture: the case of

Nigeria. Journal of Sustainable Tropical Agricultural Research. 2: 24-30 9. Oyekale, A.S. (2001): Demand and Supply Equations for Livestock Products in Nigeria: A

Simultaneous Equation Approach. Tropical Journal of Animal Science 4 (2): 117-125. 10. Oyekale, A.S., T.T. Awoyemi and Y.T. Ajose, (2001). School Children’s

Participation in Farm and Off Farm Activities: A Case Study of Akinyele Local

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Government of Oyo State. African Journal of Educational Research 7(1&2):101-110.

11. Oyekale, A.S., T.T. Awoyemi and O.I. Jaiyebo (2003). Marketing Functions and

Determinants of Profits Among Frozen Chicken Marketers in Ibadan– Oyo State. African Journal of Livestock Extension. 2:19-23.

(iii) Books, Chapters in books and articles already accepted for publication 12. Oyekale, A.S. (2003 in press) Econometric Analysis of Fish

Products Supply And Demand In Nigeria. African Journal of Livestock Extension

13. Oyekale, A.S. and A.O. Falusi (2003 in press). Determinants of Deforestation and

Agricultural Land Expansion in Nigeria. The Nigerian Journal of Economics and Social Studies

14. Oyekale A.S., T.T. Awoyemi and T.O. Ogunnupe (2003 in press). Agricultural

Intensification and Efficiency of Food Production in the Rainforest Belt of Nigeria. Agricultural Economics Special Issue on Sustainable Agricultural Intensification.

15. Oyekale, A.S., A.I. Adeoti, T.O. Ogunnupe, and T.E. Mafimisebi (2004 in press).

Land management and Economic Efficiency of Food production in Ogun and Delta State, Nigeria. Bowen Journal of Agriculture.

16. Oyekale, A.S and A.O. Falusi (2003 in press) “Agriculture, Population and

Environment Nexus in Nigeria” In Ed. A.O. Falusi Land Use and Agricultural Development in Nigeria.

17 Oyekale, A.S and J.A. Akinwumi (2003 in press) “Land Degradation and

Sustainable Agricultural Production in Nigeria” In Ed. A.O. Falusi Land Use and Agricultural Development in Nigeria.

ACADEMIC AWARDS AND GRANTS Description of Awards Year Awarded 1. University of Ibadan Postgraduate Scholarship Award 1995 2. Zard Scholarship for Agriculture, University of Ibadan. 1995/96

session 1997

3. Best M.Sc. Student in Agric. Econs. Department, U. I. 1997 4. Departmental Prize of Agric. Econs., Unibadan . 1994 5. NUPEMECO Prize for Agriculture 1994 6. Sir Kofo Abayomi Prize for Agriculture 1994 7 Rockefeller Grant to Assist Attendance at 25th IAAE

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Conference to be held at Durban, 17th –22nd August, 2003. 2003 8 PhD Dissertation Grant awarded by African Economic

Research Consortium (AERC) 2003

CONFERENCE PAPERS PRESENTED AND/OR ACCEPTED FOR PRESENTATION

• 44th Conference of Nigeria Economic Society (2002). Presented paper on “The Role of Education in Non-Farm Work Decisions in Rural Nigeria”. October 2002

• 25th Conference of the International Association of Agricultural Economists, DurbanSouth Africa. Poster Paper on “Effect of Agricultural Intensification on Food Crop Production in Southwest and Southeast Nigeria” accepted for presentation August 2003

• International Conference on Local Land use in A Globalizing World: Shaping Sustainable Social and Natural Environments, Denmark. Poster Paper on “Continuous Cropping and Efficiency of Food Production in Delta State, Nigeria” accepted for presentation. August 2003

• 1st World Conference on Agroforestry, Florida, USA. Oral paper presentation on “Land Management and Food Production Efficiency in the Rainforest Belt of Nigeria” accepted for presentation. June 2004

• Agricultural Economic Society (AES) Annual Conference. Poster paper on “A Dynamic Optimization Model for Deforestation and Agricultural Production in Nigeria” accepted for presentation. 2004

HOBBY Reading, friend making and music REFEREES Prof. J.A. Akinwumi, Department of Agricultural Economics. University of Ibadan, Ibadan.

Prof. A.O. Falusi, Department of Agricultural Economics. University of Ibadan, Ibadan.

Dr.J.O. Akintola (JP) Department of Agricultural Economics. University of Ibadan, Ibadan.

I hereby certify that information provided here are correct to the best of my knowledge. A.S. Oyekale 17th February 2004.

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CURRICULUM VITAE I. PERSONAL DATA Name: ADEOTI, Adetola Ibidunni Nationality: Nigerian Date of Birth: 15th August, 1962 Department: Agricultural Economics II. Date of Present:

Appointment: Lecturer II (15th December, 2001) Date Last Put Up For Promotion 2001 III. University Education University of Ife, Ile-Ife 1980-1985 University of Ibadan, Ibadan 1986-1987 IV. Academic Qualifications and Diplomas B. Agric (Agricultural Economics) 1985 M.Sc. (Agricultural Economics) 1987 Ph.D (Agricultural Economics) 2001 Ordinary Diploma

(Computer Techniques and Application) 1996 V. Professional Qualifications and Diplomas Nil VI. Membership of Society Member, Nigerian Society of Agricultural Economists

Member, Nigeria Participatory Rural Appraisal Network (NIPRANET) VII. Details of Teaching Experience at the University Level

Course No Course Title Unit Session AGE 201 Introduction to Computer in Agriculture 3 1997 till 2001 AGE 300 Computers in Agriculture 3 1998 till date

Other Departmental/Faculty Responsibilities

(1) Departmental Representative to the Faculty Library Committee 1997/98 Session

(2) Member of Department’s Undergraduate Committee 1999/2000 Session till date

Supervision of Students

Completed In Progress B.Sc. 10 5

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VIII. Research Completed (1) Adoption of Agroforestry Practices in Saki Area of Oyo North. (2). Fertilizer Distribution and Supply to Farmers in Oyo State.

Research In Progress (1) Economic Analysis of Irrigated and Rainfed Production Systems in Kwara State,

Nigeria. (2) Determinants of Foreign Direct Investment in Agriculture. (3) Gender Issues in Poverty Reduction in Agriculture.

Dissertation and Thesis (1) Implementation of the Land Use Act and its Effect on Rural Land Market in Abeokuta

Local Government Area, Ogun State. Unpublished B. Agric project, 1985 in the Department of Agricultural Economics, Obafemi Awolowo University.

(2) Short-Run Effect of SFEM on Some Selected Agro-allied Industries in Ibadan Area of

Oyo State. Unpublished M.Sc. Project, 1987 in the Department of Agricultural Economics, University of Ibadan, Nigeria.

(3) Resource Utilization and Efficiency of FADAMA Users in Oyo State Nigeria. PhD

Thesis in the Department of Agricultural Economics, University of Ibadan, Ibadan, Nigeria. 2001.

IX. Publications Books or Chapter in Books already published. Nil Articles Accepted For Publication. (1) Adeoti A.I. and Adenegan, K.O. (2000): Vegetable Marketing as a Strategy for Poverty

Alleviation among Urban Women. Proceeding 16th Annual Conference of Agricultural Extension Society of Nigeria April 10-12.

(2) Adeoti , A . I (2001): Womens’ Demand and Control of Agricultural Credit in Akinyele

Local Government Area, Oyo State. Nigerian Agricultural Development Studies.Vol.1 No. 2

X. Conference Attended with Paper Read (1) Adegeye, A.J. and Adeoti A.I. (1998) Assessment of Technical and Economic Efficiency

in Agricultural Programmes. National Centre for Economic Management and Administration (NCEMA), Ibadan June 15-26.

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CURRICULUM VITAE

PERSONAL DATA Name: Tolulope Olayemi OGUNNUPE Sex: Female Date of Birth: 20th November 1971 Place of Birth: Ijebu Ode State of Origin: Ogun Nationality: Nigerian Marital Status: Single Contact/ Postal Address: C/O Mr. A. S. Oyekale, Department of Agricultural Economics, University of Ibadan, Ibadan. Tel: 08037194863 E-Mail Address: [email protected] INSTITUTIONS ATTENDED WITH DATE

Our Lady Apostles’ Secondary School, Ijebu Ode, Ogun State 1983-1990 University of Agriculture, Abeokuta, Ogun State 1994-2000 University of Ibadan, Ibadan. 2002-2003 ACADEMIC QUALIFICATIONS

West African School Certificate (WASC) 1994 B.Agric. (Agricultural Economics and Farm Mgt.) 2000 M.Sc. (Agricultural Economics) 2003

WORK EXPERIENCE (i). Clerical Officer (Ijebu Ode Local Government Education Authority) Job Description: Library book cataloguing, sorting and management.

January 1992- January 1993 (ii). Teacher: (Community Secondary School, Ugwogo-Nike - NYSC)

Job Description: Taught Agricultural Science in JS2, SS1, and SS2 and supervision of students. Directly responsible to the principal and vice principals for administrative assignments that concerned the school.

July 2000 – July 2001 (iii). Teacher: (Nickdel College International, Akobo, Ibadan)

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Job Description: Teaching Agricultural Science in JS1, JS2, JS3, SS1, and Social Studies in JS1. Class teacher to SS1 and SS2. Member of school loan administration committee and school prefect monitoring committee. Responsible directly to the Proprietor, Principal, and Head of Department for other administrative assignments. March 2003 – Date.

RESEARCH PROJECTS

1. Ogunnupe T.O. (2000). Optimal Farm Plan for Small Scale farmers in Odogbolu Local Government Area: A Linear Programming Approach. B. Agric Project in the Department of Agricultural Economics and Farm Management, University of Agriculture, Abeokuta, Ogun State.

2. Ogunnupe, T.O. (2003). Forecasting the Nigeria Grain Output. M.Sc. Project in the

Department of Agricultural Economics, University of Ibadan, Ibadan. PUBLICATION Oyekale, A.S. and T.O. Ogunnupe (2003). Continuous Cropping and Efficiency of Food

Crop Farmers in Delta State, Nigeria. Paper accepted for presentation and published in the proceedings of the International Conference on Land Use Strategies in a Globalizing World, Denmark, August 21-23, 2003.

Paper Submitted For Publication In Learned Journal Oyekale, A.S. T.T. Awoyemi and T.O. Ogunnupe (under review): Agricultural

Intensification and Efficiency of Food Production in the Rainforest Belt of Nigeria. Paper submitted for special issue on “Sustainable Agricultural Intensification” by the Agricultural Economics.

ACADEMIC AWARD: Best female farmer of the year (UNAAB) 1999 HOBBY: Singing and sporting REFEREES: Prof. A.O. Falusi, Dept. of Agric Econ. University of Ibadan. Ibadan.

Dr. J.O Akintola, Dept. of Agric Econ. University of Ibadan. Ibadan.

Dr. S.A.Yusuf, Dept. of Agric Econ. University of Ibadan. Ibadan.