1

OSEVWE LAWRENCE OHWOTEMU

PG/M.SC/07/42672

PG/M. Sc/09/51723

A DISTRIBUTIONAL ANALYSIS OF INCOME IN NIGERIA

ECONOMICS

A THESIS SUBMITTED TO THE DEPARTMENT OF ECONOMICS, FACULTY OF ARTS,

UNIVERSITY OF NIGERIA NSUKKA

Webmaster

Digitally Signed by Webmaster’s Name

DN : CN = Webmaster’s name O= University of Nigeria, Nsukka

OU = Innovation Centre

AUGUST, 2010

2

A DISTRIBUTIONAL ANALYSIS OF INCOME IN NIGERIA

BY

OSEVWE LAWRENCE OHWOTEMU

PG/M.SC/07/42672

DEPARTMENT OF ECONOMICS,

UNIVERSITY OF NIGERIA,

NSUKKA

AUGUST, 2010

3

A DISTRIBUTIONAL ANALYSIS OF INCOME IN NIGERIA

BY

OSEVWE LAWRENCE OHWOTEMU

DEPARTMENT OF ECONOIMICS

A PROJECT REPORT SUBMITTED TO THE DEPARTMENT

OF ECONOMICS, UNIVERSITY OF NIGERIA, NSUKKA, IN

PARTIAL FULFILMENT OF TIIE REQUIREMENTS FOR

THE AWARD OF THE DEGREE OF MASTER OF SCIENCE

IN ECONOMICS.

SUPERVISOR: DR. H. E. ICHOKU

AUGUST, 2010

4

APPROVAL PAGE This Project Report has been approved for the award of the Degree of Master of Science

(M.Sc) of the Department of Economics, University of Nigeria, Nsukka.

…………………………… .…………………………

Dr. H. E. Ichoku Prof. C. C. Agu

Supervisor Head of Department

………………………………………..

Prof. E. O. Ezeani ---------------------------

Dean, Faculty of Social Science External Examiner

5

DEDICATION This study is dedicated to the blessed memory of my uncle Sir Osevwe Omonigho for

everything he stood for and making me who I am today, may his soul and the souls of all the

departed rest in perpetual peace, amen.

6

ACKNOWLEDGEMENT

How can one ever acknowledge academic debts satisfactorily? Knowledge is as a result of

a cumulative process spanning over many years and during these periods, the individual

passes through many people, institutions and ideas. It is difficult to categorize these people,

ideas and institutions and where the influence of one stops, that of the other begins. But all

the same, I wish to express my profound gratitude and apparent happiness to my supervisor,

Dr. H. E. Ichoku for the approval of this catchy topic and accepting the responsibility of

supervising this work. I am indebted to him in three reasons.

Firstly as my lecturer, I have been privileged to benefit from his inspiring lectures,

Secondly as my project supervisor; he has shown deep and devoted concern to this research

by making invaluable suggestions and painstaking guidance through reading the manuscript

at all stages, improving the organisation, style and clarity and thirdly, his cordial approach to

my problems and explaining some of the complex aspect of this research work, gave me the

confidence and courage to complete it in spite of odds.

My gratitude goes to the academic staff of the department of Economics whose reactions

in the proposal of this research provided the guidance and support needed in the arrangement

and preparation of this project.

I thank profusely all the non-academic staff of the department for their friendliness and

assistance in one way or the other.

To my mother- Osevwe Mary, my Cousins Bros Cosmas and Onos, my beloved wife-

Mabel, my half brother - Oke, and my dear sisters Rev. Sr. Monica, Franca and Elo. I owe

everything for their encouragement throughout this programme. I acknowledge the effort of

my friends Innocent (SPG), Mmadu Ben, Ayuba, Felix, Madu Ken, Ewubare Innocent and

colleagues Ndidi, Mrs. Oru, Micheal (okafor‘s theory), Ijeoma, Amuche, Arizona, Ify, Lizzy,

Sam, Austin, Tony and Olembe.

Finally, I am grateful to the Lord Almighty for granting me the stamina to withstand the

wears and tears, I Had to go through before completing this research.

Department of Economics,

University of Nigeria, Nsukka.

August, 2010.

Osevwe Ohwotemu Lawrence

7

TABLE OF CONTENTS TITLE PAGE

…………………………………………………………………………………...i

APPROVAL PAGE

……………………………………………………………………………ii

DEDICATION

…………………………………………………………………………………iii

ACKNOWLEDGEMENT

……………………………………………………………………..iv

TABLE OF CONTENTS

……………...……………………………………………………….v

ABSTRACT

…………………………...……………………………………………………….vi

C HAPTER ONE – INTRODUCTION

……….……………………………………………....1

1.1 Background of Study

…………………..…………………………………………………1

1.2 Problem Statement

…………………………..……………………………………………3

1.3 Research Objectives

……………………………………….............……………………….5

1.4 Hypotheses

…………………….…………………………………………………………...5

1.5 Significance of the Study

………….……………………………………………………….5

1.6 Scope of the study

…………………….……………………………………………………6

CHAPTER TWO – Nigerian Economy

………….…………………………………………….7

Performance of the Economy

…………………………………………………………………10

CHAPTER THREE – LITERATURE REVIEW

…………………………………………….13

3.1 Introduction

……………………………………………………………………………….13

3.2 Theoretical Literature

…………………………………………………………….……….13

3.3 Empirical Literature

……………………………………………….....................…...........29

CHAPTER FOUR – METHODOLOGY

………………………….…………………………35

4.1 Introduction

…………………………………………………….…………………………35

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4.2 Model Definition

…………………………………………………..……………….……..36

4.3 Techniques of Evaluation

…………………………………………..……………………..37

4.4 Model Derivations

…………………………………………………..………….…………39

4.5 Sources of Data

………………………………………………………..…………….…….41

CHAPTER FIVE - ANALYSIS OF RESULTS

…………………………..…………….........42

5.1 Introduction

……………………………………………………………..……………..….42

5.2 Analyses of Results

………………………………………………………..………….…..42

CHAPTER SIX - SUMMARY RECONMMENDATION AND CONCLUSION

…...…..…63

6.1 Summary

……………………………………………………………………...........…..…63

6.2 Recommendations

…………………………………………………………………...…....64

6.3 Conclusion

…………………………………………………………………………..…....66

REFERENCES

APPENDIX

9

ABSTRACT

Reducing poverty and inequality in the developing world continues to be a major public

policy challenge, and one that is complicated by the lack of a generalized comprehensive

strategy for dealing with it. Putting the combat against poverty to the forefront as the main

objective of the development process has raised the issue of the linkage between inequality

and poverty. There is now a growing agreement that booth the rate and the distributional

impact of income are important in fighting poverty. This paper analyzes the trend in income

distribution in Nigeria and examines the issue of inequality in expenditure among households

as well as urban-rural difference in consumption among households and further examines

geopolitical zone inequality in Nigeria. That is, the decomposition analysis was divided into

two categories. The first category is concerned with the decomposition of households‘

expenditure. This underscores the contributions of these components to overall inequality and

may help in the design of effective economic and social policies to reduce inequality and

poverty in Nigeria. The second category of decomposition analysis dealt with the breakdown

of expenditure into population sub-groups (This approach starts with the division of a sample

into discrete categories; for instance, rural and urban residents, gender, age group, education

level of household heads, household size, occupation, states and geopolitical zones), and then

follows with the estimation of the level of inequality using Gini coefficient while the Lorenz

curve is used to measure changes in the income distribution. The analysis builds on a survey

of 19158 households in Nigeria, which was conducted by the Nigeria living Standard Survey

(NLSS) 2004 of the National Bureau of Statistics.

The results of our analysis indicate that factors such as age, gender, and education level of

the household head are important factors in explaining inequality profile in the country. We

however found that inequality exists in the rural and urban areas but more of the rural areas

10

and inequality is very high in some of the geopolitical zones. This thus suggests policies that

will alleviate poverty in the rural and urban areas as well as policies to reduce inter

geopolitical zone access to opportunities. We further observed from the Lorenz curve that

17.95 percent of the households controlled 46.7 percent of the total expenditure which means

almost quarter of the total of the household controlled almost half of the wealth of the Nation.

11

CHAPTER ONE

1.1 BACKGROUND OF STUDY

Poverty and income inequalities are two of the important disturbing factors on the way to

development in developing countries. Rising inequality threatens growth and poverty

reduction targets (Olaniyan and Awoyemi, 2005). A recurring issue in discussions on

development is whether the main focus of development strategies should be placed on growth

or poverty, and/or on inequality (Bourguignon, 2003). Although there is a general consensus

among economists that economic growth is good for the poor, the debate continues on

whether economic growth is sufficient for poverty reduction (Morale, 2006).

In the recent literature, growth and distribution is a lens through which we can investigate

the complex interplay of the factors explaining the nature and causes of the wealth of nations:

population growth; structural change: technological progress; and physical, social, and human

capital accumulation.

Enhancing the well-being of the less well-off and reducing inequalities have become the

principal targets of the development process. The United Nations General Assembly in New

York notably confirmed these aims in September 2000, when some 189 countries approved,

in the context of the Millennium Development Goals (MDGs), that fighting poverty in all its

aspects is the major challenge of the international community. To achieve substantial

progress in poverty reduction, most governments and international organizations now agree

on both the importance of economic growth and on the need for economic growth to be

biased in favor of the poor. Undeniably, absolute poverty is bound to decrease whenever

economic growth positively affects the income distribution of the poor. However, it is

presumably not the only requirement. Policy makers with an interest in poverty reduction are

12

also concerned with the distribution of growth rates amongst the population. This is important

because the distribution of any increment to growth will determine the rate at which

economic growth is converted into poverty reduction. More precisely, the larger the share of

any increment to growth captured by the poor, the higher the pro-poorness feature of

economic growth (Sami, 2006).

The relationship between economic growth and poverty reduction is thus of direct

relevance to the challenge of fighting poverty in all its aspects. There is growing evidence

that achieving both high and equitable growth is strengthening the linkage between growth

and poverty reduction. This represents a major departure from the trickle-down development

approach whereby economic growth benefits the more affluent in the first stages of the

development process, followed by the less well-off because of the rise in the expenditures of

the rich. This means that the development process will be accompanied by a rise in the

inequalities since the poor benefit less proportionately from economic growth than do the

non-poor.

Poverty and income inequality are closely related and it has been argued that income

inequality is a manifestation as well as a strong cause of poverty (UNU/WIDER, 2000).

Kolenikov and Shorrocks (2003), found that the high level of poverty in the late 1990‘s in

Russia was due more to the rise in income inequality than to decline in average income.

When economic growth increases, poverty rate decreases, but as income inequality increases,

the incidence of poverty also increases. Because of the linkage between income inequality

and poverty, reducing income inequality has become a major public policy challenge among

development agencies and poverty reduction experts. Yet, in most developing countries,

discussions about poverty reduction strategies often focus almost exclusively on income

growth, neglecting the potential roles of income redistribution and inequality (UNU/WIDER,

13

2000). Most of the discussions often fail to recognize that, to achieve reduction in poverty,

income growth has to be equitably distributed. It is understood that fighting poverty cannot

be continuously relied on redistributive policies in absence of sustainable economic growth.

However, there is plenty of evidence suggesting that high rates of growth accompanied with

progressive distributional changes will be more effective in reducing poverty than growth

patterns that leave the income distribution unchanged. Similarly, even if the poor were to

benefit from growth as much as the non-poor, the initial distribution of income would still

determine the rate of poverty reduction. The higher the level of inequality, the weaker the

linkage between poverty reduction and growth; and the higher the growth rate needed to

reach a given target of poverty reduction.

That growth is good for the poor is debatable. But the real questions is, has economic

growth been pro-poor or pro-rich over the years and what is the distributional trend of

household income and the level of income inequality in Nigeria. Answering these questions is

the principal objective of this research. This research seeks to review the analysis of income

distribution in Nigeria using secondary data covering the period 1993 to 2008.

1.2 PROBLEM STATEMENT

One of the most challenging themes for economists is to explain ―how countries become

rich‖ (Tridico, 2006). Nigeria may be the most challenging and important developing country

in the world today. It has the smallest manufacturing sector of any large economy in the

world, and the greatest concentration of export and government revenue dependence on a

natural resource commodity. It is a country of spectacularly failed economic policies, whose

GDP per capita is no higher than it was forty years ago. It is a country of rising poverty and

increasing income inequality (King, 2003). Achieving equitable distribution of income and

14

alleviation of poverty has for some time been a major development objective. Studies have,

therefore, especially in the 1970s, appraised development policies in terms of how far these

objectives are being realized.

In the 1980s many less developed countries (LDCs) introduced SAPs in an effort to

promote growth and redress the negative trends in a number of economic indicators. Studies

have found that adjustment policies have had negative impact on some socioeconomic

groups. Recently the depth and severity of extreme poverty in Nigeria has been alarming.

And over the years, the government undertook some macroeconomic policies with the aim of

reducing, if not totally eradicating poverty. These policies were expected to at least raise the

standard of living of Nigerians. The impact of these policies on alleviating poverty has been

contentious. Some studies in the past have argued that the poor has benefited more from these

policies (Obadan, 1994; Faruquee, 1994); while some found that there was positive real

growth yet poverty and inequality still worsened (Aigbokhan, 2000). There is now a growing

agreement that both the rate and the distributional impact of growth are important in fighting

poverty. This means that pro-poorness of a given growth rate is more important in certain

cases than in others.

The Nigerian problem in the 20th century has been the inability to get the best from her

human resources (World Bank, 2000). The problem goes beyond low income, savings and

growth. It includes high inequality, which includes among others, unequal access to basic

infrastructure and unequal capabilities (education and health status). Incidentally, the

importance of unequal access to opportunities, assets, income and expenditure cannot be

overemphasized as it plays important roles in reducing poverty and spurring the economy to

long-term development. Nigeria has experienced a high incidence of poverty over the last two

decades (Olaniyan and Awoyemi, 2005). The impact of the incidence becomes more

important because of the high inequality associated with even this low level of household

income and expenditure. This is precisely the approach followed in this paper. It is based on

this that this study seeks to answer the following questions;

15

What is the distributional impact of income in Nigeria?

What is the level of income inequality in Nigeria?

1.3 RESEARCH OBJECTIVES

The broad objective of this study is to investigate the trend in the income distribution in

Nigeria. Specifically this study seeks to:

To examine the level of income inequality in Nigeria,

To examine the pattern of income distribution in Nigeria,

Estimate the level of poverty in Nigeria,

1.4 HYPOTHESES

The following hypotheses will be tested in this study:

Ho1. There is no significant difference in the impact of income distribution on poverty in

Nigeria.

Ho2. Inequality does not affect poverty.

1.5 SIGNIFICANCE OF THE STUDY

One of the pathetic features of the Nigerian economy today is that a majority of its

populace is living in a state of destitution while the remaining relatively insignificant

minority is living in affluence (Osinubi and Gafaar, 2005). An important objective of this

paper is to carry out analysis of the impact of income and distribution on changes in poverty

in Nigeria and further attempts to provide an update on household expenditure inequality in

Nigeria.

16

This is intended to serve as a tool for explaining the economic performance in Nigeria.

The issue of polarization in income distribution will be specifically investigated and its

influence on poverty will be inferred. This would constitute a major contribution of the study

and further this paper will proffer solutions to findings on the issues above. In this respect,

the study contributes to knowledge on poverty in Nigeria.

The exploration of these factors is expected to raise some policy issues and give policy

directions to policymakers especially concerning the identification of the target groups that

will enhance more equitable distribution of income among Nigerian households. This will not

only reduce inequality but also help the poorest of the poor to contribute to and benefit from

the growth and development process.

1.6 SCOPE OF THE STUDY

The period covered by this research is from, 1993 – 2008. The choice is guided by the

availability of data.

17

CHAPTER TWO

Nigerian Economy

The Federal Government on 23 January, 2009 in Abuja reiterated its stance that the

nation‘s economic outlook remained very favourable, in spite of current global financial

crisis.

Former President Umaru Yar‘Adua, gave the re-assurance while declaring open the 3rd

Annual Micro-Finance Conference/Entrepreneurship Awards, organised by the Central Bank

of Nigeria (CBN). He stated that the Federal Government had taken many bold and pragmatic

steps to shield the economy from the negative effects of the global meltdown. ―Our economic

growth is on track, buoyed by the strong performance of the non-oil sector. The provisional

estimate of Nigeria‘s GDP growth rate for the end of 2008 is an impressive 6.8 percent,

compared with a 6.2 percent in 2007‖ he said.

Nigeria‘s economy is struggling to leverage the country‘s vast wealth in fossil fuels in

order to displace the crushing poverty that affects about 57 percent of its population.

Economists refer to the coexistence of vast natural resources wealth and extreme personal

poverty in developing countries like Nigeria as the ―resource curse‖. And according to

Odularu (2008), Nigeria‘s exports of oil and natural gas at a time of peak prices have enabled

the country to post merchandise trade and current account surpluses in recent years.

18

Reportedly, 80 percent of Nigeria‘s energy revenues flow to the government, 16 percent

covers operational costs, and the remaining 4 percent go to investors. However, the World

Bank has estimated that as a result of corruption 80 percent of energy revenues benefit only

one percent of the population. During 2005 Nigeria achieved a milestone agreement with the

Paris Club of lending nations to eliminate all of its bilateral external debt. Under the

agreement, the lenders will forgive most of the debt, and Nigeria will pay off the remainder

with a portion of its energy revenues. Outside the energy sector, Nigeria‘s economy is highly

inefficient. Moreover, human capital is underdeveloped Nigeria ranked 151 out of 177

countries in the United Nations Development Index in 2004 and non-energy-related

infrastructure is inadequate.

During 2003–2007, Nigeria has attempted to implement an economic reform program

called the National Economic Empowerment Development Strategy (NEEDS).

The purpose of NEEDS is to raise the country‘s standard of living through a variety of

reforms, including macroeconomic stability, deregulation, liberalization, privatization,

transparency, and accountability. NEEDS addresses basic deficiencies, such as the lack of

freshwater for household use and irrigation, unreliable power supplies, decaying

infrastructure, impediments to private enterprise, and corruption. The government hoped that

NEEDS would create 7 million new jobs, diversify the economy, boost non-energy exports,

increase industrial capacity utilization, and improve agricultural productivity. A related

initiative on the state level is the State Economic Empowerment Development Strategy

(SEEDS).

A long-term economic development program is the United Nations (UN) sponsored

National Millennium Development Goals for Nigeria. Under the program, which covers the

years from 2000 to 2015, Nigeria is committed to achieve a wide range of ambitious

19

objectives involving poverty reduction, education, gender equality, health and environment.

In an update released in 2004, the UN found that Nigeria was making progress toward

achieving several goals but was falling short on others. Specifically, Nigeria had advanced

efforts to provide universal primary education, protect the environment, and develop a global

development partnership. However, the country lagged behind on the goals of eliminating

extreme poverty and hunger, reducing child and maternal mortality, and combating diseases

such as human immunodeficiency virus/acquired immune deficiency syndrome (HIV/AIDS)

and malaria.

A prerequisite for achieving many of these worthwhile objectives is curtailing endemic

corruption, which stymies development and taints Nigeria‘s business environment.

Corruption mostly harms Nigerians themselves, but the country is widely known around the

world for a fraudulent activity known as the "Advance fee fraud" scheme, a.k.a the "419"

scam or the Nigerian scam, which seeks to extort money from foreign recipients of letters and

emails with the promise to transfer a nonexistent windfall sum of money.

The oil boom of the 1970s led Nigeria to neglect its strong agricultural and light

manufacturing bases in favour of an unhealthy dependence on crude oil. In 2000 oil and gas

exports accounted for more than 98 % of export earnings and about 83 % of federal

government revenue. New oil wealth, the concurrent decline of other economic sectors, and a

lurch toward a statistics economic model fueled massive migration to the cities and led to

increasingly widespread poverty, especially in rural areas. A collapse of basic infrastructure

and social services since the early 1980s accompanied this trend. By 2000 Nigeria's per capita

income had plunged to about one-quarter of its mid-1970s high, below the level at

independence. Along with the endemic malaise of Nigeria's non-oil sectors, the economy

continues to witness massive growth of "informal sector" economic activities, estimated by

some to be as high as 75 % of the total economy.

20

The U.S. remains Nigeria's largest customer for crude oil, accounting for 40% of the

country's total oil exports; Nigeria provides about 10% of overall U.S. oil imports and ranks

as the fifth-largest source for U.S. imported oil.

The United States is Nigeria's largest trading partner after the United Kingdom.

Although the trade balance overwhelmingly favors Nigeria, thanks to oil exports, a large

portion of U.S. exports to Nigeria is believed to enter the country outside of the

Nigerian Government's official statistics, due to importers seeking to avoid Nigeria's

excessive tariffs. To counter smuggling and under-invoicing by importers, in May 2001 the

Nigerian Government instituted a 100 % inspection regime for all imports, and enforcement

has been sustained. On the whole, Nigerian high tariffs and non-tariff barriers are gradually

being reduced, but much progress remains to be made. The government also has been

encouraging the expansion of foreign investment, although the country's investment climate

remains daunting to all but the most determined. The stock of U.S. investment is nearly $7

billion, mostly in the energy sector. Exxon Mobil and Chevron are the two largest U.S.

corporate players in offshore oil and gas production. Significant exports of liquefied natural

gas started in late 1999 and are slated to expand as Nigeria seeks to eliminate gas flaring by

2008, as a target which was not achieved.

Oil dependency and the allure it generated of great wealth through government contracts,

spawned other economic distortions. The country's high propensity to import means roughly

80 % of government expenditures is recycled into foreign exchange.

Cheap consumer imports, resulting from a chronically overvalued Naira, coupled with

excessively high domestic production costs due in part to erratic electricity and fuel supply,

have pushed down industrial capacity utilization to less than 30 %. Many more

Nigerian factories would have closed except for relatively low labor costs (10 % - 15 %).

Domestic manufacturers, especially pharmaceuticals and textiles, have lost their ability to

21

compete in traditional regional markets; however, there are signs that some manufacturers

have begun to address their competitiveness.

PERFORMANCE OF THE ECONOMY

The Nigerian economy has had a truncated history. In the period 1960-70, the Gross

Domestic Product (GDP) recorded 3.1 per cent growth annually. During the oil boom era,

roughly 1970-78, GDP grew positively by 6.2 per cent annually - a remarkable growth.

However, in the 1980s, GDP had negative growth rates. In the period 1988-1997 which

constitutes the period of structural adjustment and economic liberalisation, the GDP

responded to economic adjustment policies and grew at a positive rate of 4.0. In the years

after independence, industry and manufacturing sectors had positive growth rates except for

the period 1980-1988 where industry and manufacturing grew negatively by - 3.2 per cent

and - 2.9 per cent respectively. The growth of agriculture for the periods 1960-70 and 1970-

78 was unsatisfactory. In the early 1960s, the agricultural sector suffered from low

commodity prices while the oil boom contributed to the negative growth of agriculture in the

1970s. The boom in the oil sector lured labour away from the rural sector to urban centres.

The contribution of agriculture to GDP, which was 63 percent in 1960, declined to 34 per

cent in 1988, not because the industrial sector increased its share but due to neglect of the

agricultural sector. It was therefore not surprising that by 1975, the economy had become a

net importer of basic food items. The apparent increase in industry and manufacturing from

1978 to 1988 was due to activities in the mining sub-sector, especially petroleum. Capital

formation in the economy has not been satisfactory. Gross domestic investment as a

percentage of GDP, which was 16.3 percent and 22.8 percent in the periods 1965-73 and

1973-80 respectively, decreased to almost 14 percent in 1980-88 and increased to 18.2

22

percent in 1991 -98. Gross National Saving has been low and consists mostly of public

savings especially during the period 1973-80. The current account balances before official

transfers are negative for 1965-73, 1980-88 and 1991-98.

The table below shows the break down of sectoral contribution to GDP in percentages.

SECTORAL CONTRIBUTION TO GDP %

ACTIVITY SECTOR 1999 2000 2001 2002 2003 2004 2005

1. Agriculture 47.6 35.84 35.58 35.86 34.63 40.99 41.49

(a) Crop Production 37.99 29.89 29.66 29.86 28.98 36.48 36.95

(b) Livestock 6.06 3.48 3.42 3.47 3.28 2.6 2.63

(c) Forestry 1.4 0.78 0.76 0.74 0.68 0.54 0.54

(d) Fishing 2.15 1.69 1.74 1.79 1.69 1.37 1.37

2. Industry 19.77 36.98 37.3 34.67 38.16 29.48 27.72

(a) Crude Petroleum 12.47 32.45 32.65 29.75 33.44 25.72 23.82

(b) Mining & Quarrying 0.37 0.29 0.31 0.31 0.3 0.26 0.27

(c) Manufacturing 6.93 4.24 4.34 4.61 4.42 3.5 3.63

3. Building & Construction 2.46 1.95 2.09 2.11 2.08 1.44 1.53

4. Wholesale & Retail Trade 13.62 13.11 12.85 13.22 12.68 12.9 13.74

5. Services 29.75 12.12 12.17 14.12 12.45 14.56 14.88

(a) Transport 3.64 2.28 2.28 2.59 2.38 2.38 2.41

(b) Communication 0.37 0.11 0.13 0.19 0.21 1.14 1.4

(c) Utilities 0.61 0.44 0.46 0.54 0.52 3.58 3.6

(d) Hotel & restaurant 0.57 0.21 0.21 0.21 0.2 0.37 0.39

(e) Finance & Insurance 11.16 5.2 5.2 6.5 5.34 4.08 3.98

(f) Real Estate & Business Services 0.35 1.9 1.91 1.9 1.78 1.34 1.41

(g) Producers of Govt. Services 11.06 1.25 1.22 1.35 1.24 0.96 0.95

(h) Comm., Social & Pers. Services 1.99 0.73 0.76 0.84 0.78 0.71 0.74

23

Source- Nigeria: Economics Growth Drivers and Financial Challenges by Soludo (2006)

CHAPTER THREE

LITERATURE REVIEW

3.1: Introduction

The related literature has been reviewed under the following sub-headings.

1. Theoretical literature on

Neoclassical Theories of Growth

Endogenous Growth Theories

Pro-poor Growth

Measures of Inequality

2. Empirical literature

3.2: THEORETICAL LITERATURE

24

Economic Growth is not an automatic birthright for an economy. For an economy to

grow, it has to create the right conditions for growth. Growth depends to a significant extent

on the resources a country has. The better the quantity and the quality of the resources the

more potential it has to grow (Moses, 2008).

All economic theories have said something about the relationship between growth and

both income and wealth distribution, which has long been the subject of controversy. These

theories have been used to test whether or not aspects such as foreign trade or human capital

growth contribute to increased inequality and in this way to slowed GDP growth, particularly

in developing countries. In this theoretical review, we situate economic growth within the

framework of main theories of growth namely Neoclassical theories and Endogenous growth

theories, then we look at the concept of pro-poor growth in Nigeria.

3.2:1 Neoclassical Theories of Growth

The basic Neoclassical model of growth developed by Solow (1957) and Swan (1956)

follows the logic of the Keynesian Model, like the Harrod-Domar model, the ultimate aim is

the search for the condition of a stable equilibrium. When using any economic model to

portray a real world problem and to study the effects of various resolutions, the usefulness of

the model is most contingent upon its ability to simulate the real world without excessive

oversimplification. One of the questions this may lead to is whether or not the neoclassical

growth model is a useful tool for economists and policymakers in understanding global

poverty and developing policies to reduce poverty.

The neoclassical growth model emphasizes the role of technological progress and labor

productivity in maintaining a sustained long-run rate of growth. Population growth,

depreciation of capital, and, most notably, technological progress directly affect the dynamics

25

of the growth process. One major idea that encompasses the frameworks of this model

underlines the assumption that over the long run, economic growth is independent of the

savings rate (or equivalently, investment). However, the economy experiences a transitional

state of growth or decline in the capital stock, which could be prolonged over a period of

decades, due to fluctuations in investment generated from savings that is greater or less than

required investment. In steady state, therefore, the growth rate of output is equal to the rate of

population growth and the rate of technological progress. This shows according to David

Stone (2004) that output per worker will grow at the rate of technological progress in a state

of balanced growth over the long run. The neoclassical growth model is achieved by

assuming a diminishing marginal product of capital, in which the economy gradually moves

to a point where savings provides only sufficient enough investment to cover depreciation. In

order to make saving and investment equal, we assume that the economy is closed. This is a

significant and unrealistic assumption to make, yet allows the issues of trades surpluses and

deficits to be overlooked. Taxes and government spending is also ignored in order to put

focus on the behavior of private savings. Lastly, we assume private savings to be proportional

to income.

The first idea we want to explore is whether or not the idea of economic growth is relevant

to developing policies that reduce poverty in developing countries. Indeed, the neoclassical

growth model does effectively highlight an important correlation between economic growth

and poverty reduction. This model theorizes that economic growth is contingent upon the

accumulation of capital-both human and physical-and technological progress. Human capital

refers to the increase in labor productivity due to levels of education, skills and experience,

and the health of people. Physical capital represents the tools used in production. Lastly,

technological progress has a two-fold meaning: it is the ability of larger quantities of output

to be produced with the same quantities of capital and labor. Equivalently, technological

26

progress represents the key ingredient in developing new, better and a larger variety of

products for the public to consume. Studies have shown that "literacy and other indicators of

education remain woefully low across much of the developing world," and a policy that helps

poor people acquire human capital would result in their earning higher wages (Besley and

Burgess, 2003). The neoclassical growth model could be used to argue that a climate that is

more conducive to investment and entrepreneurship would help to reduce poverty. This idea

follows from the premise that heavy regulation of business ownership is not in the public

interest because it results in low capital intensities, low human capital per worker, and low

productivity (Bigsten and Levin, 2000).

Fig 1

Steady-State Growth of Solow-Swan

27

Where Y ……….output

L …………….Labour

k…………….Capital

s…………….. Saving

I ……………Investment

n…………….Population

The above graph is use to explain Solow-Swan steady state growth, which says that the

growth rate of output is equal to the rate of population growth and the rate of technological

progress

3.2:2 Endogenous Growth Theories

The Endogenous growth models emanates from the work of Romer (1986) and Lucas

(1988). Over the last ten years, the mainstream theorists have begun to study more seriously

the relationship between distribution and growth. Although there are facts that explain it, this

reappearance in the academic world has mainly been associated with the emergence and

improvement of endogenous growth theory. Given its particular nature, scholars have usually

used this theory along with an explanation extracted from the theory of endogenous economic

policy. According to Solimano (1998), this literature rests on three methodological

assumptions. First, it reverses the direction of the causality of the Solow model and the

Kuznets curve, so that causality goes from distribution to growth. Second, the new models

28

seem to show investment driven growth. The third methodological assumption Solimano

(1998) mentions is that political mechanisms can be used to show how income distribution

affects growth. Thus, the process is not exclusively economic. For example, if there are two

targets that economic authorities have to deal with, let us say growth and equality, they might

identify the former as the most important. Nevertheless, both the specific grade of social

conflict and the political process that an economy may have will finally determine to what

degree each target is actually important and how each will be achieved. So, whereas the

economic mechanism is based on the outstanding role given to saving as the force that drives

growth, economic policies are not only a result of technocratic discussion but also of a social

and political agreement. Political mechanisms are exemplified through the introduction or

modification of income tax that negatively affects the profitability of either human or

physical capital. According to this argument, it is the relative preference for distributive

policy that determines the new higher tax burden on such inputs and therefore the lower pace

of economic growth. Hence, there is an inverse relationship between the reduction of

inequality and the rate of economic growth, which acts indirectly on growth through

investment decisions made after direct taxes have been paid.

In this theory, the political and social preferences for equality and growth policies are

revealed in the voting process. These sorts of citizen preferences are a function of the

endowments of capital, land, talents, skills, and raw labor. Consequently, in contrast to the

Keynes and Kalecki models, this theory leads to the conclusion that income concentration is

harmful for growth, for three worrisome reasons.

First, the more unequal the income distribution, the higher the income taxes and the

degree of implementation of redistributive policies, thus discouraging private accumulation

of physical and human capital.

29

Second, a high concentration of income and wealth can increase social tension and be a

source of political instability. Investment and economic growth can also be deterred in this

way.

Third, inequality of wealth impedes poor people‘s access to credit and therefore obstructs

their investing in education and other opportunities that may increase their market value as

human capital, thus slowing down investment and growth.

Solimano (1998) says that we should not be so pessimistic. The message of the Kuznets

curve, for example, is that beyond a certain threshold of income per capita, the growth

process will reduce, by itself and in the long run, differences in income distribution.

Furthermore, policies such as a broad education access program will contribute both to

economic growth and to increased income levels for a huge portion of the population. In

addition, it is known that a more equitable distribution of income and economic opportunities

also contributes to the alleviation of social conflict and political instability. However,

Solimano‘s recommendation is not acceptable because most developing countries need to

solve inequality problems immediately or in the medium term, at least. Otherwise, they might

not exist in the long run, which is what mainstream scholars are concerned about.

3.2:3 PRO-POOR GROWTHS

In the past few years, the term ―pro-poor growth‖ has become pervasive in discussions of

development policy. Despite the widespread use of the term, there appears to be much less

consensus as to what exactly pro-poor growth means, let alone what its determinants are.

According to one view, ―pro-poor growth‖ means that poverty falls more than it would

have if all incomes had grown at the same rate (Baulch and McCullock, 2000; Kakwani and

30

Pernia, 2000). This definition focuses on the distributional shifts during the growth process;

roughly speaking, for growth to be deemed ―pro-poor‖ by this definition, the incomes of the

poor should grow at a higher rate than those of the non-poor. A concern with this definition is

that rising inequality during a period of overall economic expansion may come with large

absolute gains to the poor yet this is not deemed to be ―pro-poor growth.‖ (Similarly, a

recession will be deemed pro-poor if poor people lose proportionately less than others, even

though they are in fact worse off.). The second definition, which is a broader and more

intuitive definition, is that growth is pro-poor if the poverty measure of interest falls

(Ravallion and Chen, 2003). This second definition avoids the problem of the first definition

by focusing instead on what happens to poverty. The extent to which growth is pro-poor then

depends on how much a chosen measure of poverty changes. Naturally this will depend in

part on what happens to distribution, but only in part — it will also depend on what happens

to average living standards.

Pro-Poor Growth and Poverty Reductions

Although economic growth is essential for achieving the MDGs, especially for poverty

reduction, policymakers may wonder if growth alone can improve the welfare of the poor.

For that reason, recent studies have focused on the elements of pro-poor growth. Broadly

speaking, pro-poor growth can be defined as one that enables the poor to actively participate

in and significantly benefit from the economy, economic growth inclusive. And according to

Kakwani and Pernia, 2000, Poverty reduction is about improving human well being (the life

people live, what they can do or cannot do) in particular that of the poor people. It is such that

no person in society is deprived of the minimum basic capabilities. For instance, everyone

should be adequately nourished, no child should be allowed to die prematurely, and populace

should live satisfying lives with long life span.

31

The poor have much lower well-being than the non-poor because they lack the resources

to satisfy the minimum basic necessities of life (Kakwani and Pernia, 2000). The market

forces induced growth process generally benefits the non-poor proportionally more than the

poor. This is because the non-poor have inherent advantages like human and material capital

in a market economy. Moreover, in many countries, government knowingly or unknowingly

adopts policies that are biased in favour of the rich. Consequently, the gap in well-being

between the poor and non-poor tends to persist, if not widen. Thus to foster the overall well-

being of the populace, government needs to pursue policies that will reduce this gap.

Three components can alter poverty levels over time: the rate of economic growth, the

response of poverty to that growth and changes in income distribution. However, studies

show that almost all change comes from just the rate of growth. In describing the impact of

economic growth on poverty Ravallion (2005), it can also be useful to exploit the fact that a

measure of poverty can be written as a function of the mean of the mean of the distribution on

which that measure is based and the Lorenz curve of that distribution. (The Lorenz curve

gives cumulative income shares as a function of the cumulative proportion of the population

ranked by income). So therefore, the government must focus on the types of growth strategies

that will contribute most effective to reducing poverty.

Promoting pro-poor growth requires a strategy that is deliberately biased in favour of the

poor so that the poor benefit proportionally more than the rich. Such an outcome would

rapidly reduce the incidence of poverty so that those at the bottom end of the distribution

curve of consumption would have the resources to meet their minimum basic needs. A pro-

poor growth strategy entails the removal of institutional and policy-induced biases against the

poor as well as the adoption of direct pro-poor policies. For instance, discrimination on

grounds of gender, ethnicity, and religion hurts the poor more than the rich; the same can be

32

said of artificial barriers to entry into certain trades and professions, or into the formal labour

market in general.

Macro policies that tend to constrain pro-poor growth include policies as overvalued

exchange rates, big-city-oriented industrial location policies, and public infrastructure

spending biases toward urban areas and against the welfare of the poor such as monopoly

powers enjoyed by some firms that result in high prices, subsidized public utilities (for

example, low water fees), state universities (low student fees) that benefit primarily the non-

poor, and housing policy (rent control) that limits housing supply.

Direct pro-poor policies are also required. These include adequate public spending for

basic education, health and family planning services, improved access to credit, and the

promotion of small and medium enterprises. A well-administered progressive tax system is

also pro-poor. Typically, this means a heavier reliance on personal income taxation, which is

progressive rather than on indirect taxation, which is regressive. Unfortunately, in many

developing countries revenue generation depends much on indirect than on direct taxes.

However, computing the extent to which growth is pro-poor is a hotly debated subject. For

instance, Ravallion and Chen (2003), and Kraay (2004), describe growth as pro-poor

whenever it decreases the poverty index of interest. Kakwani and Pernia (2000), Son (2004),

and Kakwani and Son (2006), believed that poverty-reducing growth cannot be a sufficient

condition for pro-poorness. The growth process should also benefit the poor proportionately

more than the non-poor. Lopez (2004) and Osmani (2005) find these two definitions of pro-

poorness problematic. They argue that the distributional impact of growth is not all that

matters. For instance, Kakwani and Pernia‘s (2000) definition could conflict with the Pareto

principle as an equitable low growth rate can be judged more pro-poor than an inequitable

33

high growth rate even if the former yields less absolute poverty reduction than the latter.

Osmani (2005), stated that if the nature of growth (that is, its distributional impact) is what

we are after, why bother to coin a new term pro-poorness growth? We already have the

concept of equitable growth, which requires growth to be such as to benefit the poor,

proportionately more than the rich.

3.2:4 MEASURES OF INEQUALITIES

A substantial and growing literature develops various measures or indexes of economic

inequality. Some use the Gini coefficient or other measures or relationships drawn from

Lorenz curves; some prefer different indicators of dispersion, such as an entropy index; some

offer axiomatic derivations of inequality indexes; and still others advocate the use of

normative measures derived from social welfare functions. These measures of inequality that

have been proposed in the literature are grouped into two classes known as:

the descriptive or positive measures and

Normative measures of inequality.

For the purpose of this research, we will discuss the descriptive measure of inequality.

The descriptive or positive measure of inequality is a measure that may be used in

regressions relating inequality and growth — measurement often is necessary. But what

counts as a good measure depends on the economic theory and empirical facts in particular

contexts, not (necessarily) on the properties and axioms that have generally been proposed for

measures of inequality. A few of more important descriptive measures are discussed below.

Range

34

Consider distributions of income over n persons, i=1…,n, let yi be income of person i and

let the average level of income be µ.

The range can be defined as the gap between two observation, it is perhaps based on comparing

the extreme values of distribution, i.e., the highest and the lowest income level if our focus is on

income distribution. It is calculated by subtracting the smallest observation from the greatest.

R = ymax – ymin

Where R is the range and ymax and ymin are, respectively the maximum and minimum

value of income.

It is measured in the same units as the data. Since it only depends on two of the

observations, it is a poor and weak measure of dispersion except when the sample size is

large. The difficulty with the range is evident. It ignores the distribution in between the

extremes. Therefore by concentrating on the extreme values only, the range misses important

features of the distribution.

Relative Mean Deviation

The relative mean deviation is a way of looking at the entire distribution and not merely

at the extreme values, it is to compare the income level of each with the mean income, to sum

the absolute value of all the differences, and then to look at that sum as a proportion of total

income, i.e. the average absolute distance of everyone‘s income from the mean, expressed as

a proportion of the mean.

M = ∑ni=1 │µ - yi│nµ

35

With perfect equality M = 0, and with all income going to one person only, M = 2(n –

1)/n.

The main problem with the relative mean deviation is that it is not at all sensitive to

transfers from a poorer person to a richer person (Pigou-Dalton condition) as long as both lie

on the same side of the mean income. The limitation is that it does not recognise whether the

transfer is at the low income or high income level but it do recognise that there is a transfer.

The Variance and the Coefficient of Variation

The variance is a measure of how spread out a distribution is. It is a measure of

variability.

The variance is computed as the average squared deviation of each number from its mean.

The formula (in summation notation) for the variance in a population is

V = ∑ni=1 (µ - yi)

2/n

It is summation of the square of the distribution, and this would have the result of

accentuating differences further away from the mean, so that a transfer from a relatively rich

person to the relatively poor person would decrease the inequality gap. This enhances Pigou-

Dalton condition as a result of the squaring.

We must understand that the variance depends on the mean income. One distribution A

may show much greater relative variation than B and still A may end up with lower variance

if mean of A around which the variation take place is smaller than mean of B. A measure that

36

does not have this deficiency and concentration on relative variation is the coefficient of

variation, which is simply the square root of the variance divided by the mean income level:

C = V1/2/µ

The coefficient of variation represents the ratio of the standard deviation to the mean, and

it is a useful statistic for comparing the degree of variation from one data series to another,

even if the means are drastically different from each other. While the coefficient of variation

captures the property of being sensitive to income transfers for all income levels and, is

independent of the mean level.

The Standard Deviation of Logarithms

The logarithm recommends income transfers at the lower end which is done by taking

some transformation of incomes that staggers the income levels. Logarithm in contrast with

taking the variance or the standard deviation of actual values, is that it eliminates the

arbitrariness of the units and therefore of absolute levels, since a change of units, which takes

the form of a multiplication of the absolute values, comes out in the logarithmic form as an

addition of a constant, and therefore goes out in the wash when pair wise differences are

being taken.

Logarithm reduces the large differences by rescaling the absolute values into relative.

Note that in the standard statistical literature, the deviation is taken from the geometric mean

rather than the arithmetic mean, but in the income distribution literature using the arithmetic

mean seems more common.

H = [∑ni=1 (logµ - logyi)

2/n ]1/2

37

The fact that a logarithmic transformation staggers the income levels tends to soften the

blow in reflecting inequality since it reduces the deviation, but on the other hand it has

property of highlighting differences at the lower end of the scale.

The logarithm suffers some weaknesses which are:

Firstly, as income levels get higher and higher, they suffer more contraction. This make

the result in the social welfare functions not concave. Secondly, H depends on the arbitrary

squaring of formula, although, this is done after log transformation. Thirdly, it also shares

limitations of the variance and coefficient of variance taking the difference of individual from

the mean.

Lorenz curve

Lorenz curve is propounded by max Lorenz in 1905. Lorenz curve is an important tool for

the analysis of inequality in a variety of situations – inequality in the distribution of income

within a population, inequality in the productivity of scientists in a give population,

inequality in the allocation of research grants to different institutions by a funding agency,

etc. It is a graphical device used to represent distributional inequality. When all the members

of the population receive the same income, the Lorenz curve is equi-distribution or identity

function. The Lorenz curve bends downward to the right, as the distribution of income

becomes more unequal as illustrated below;

38

For a perfectly equal distribution, there would be no area between the 45 degree line and

the Lorenz curve -- a Gini coefficient of zero. For complete inequality, in which only one

person has any income (if that were possible) the Lorenz curve would coincide with the

straight lines at the lower and right boundaries of the curve, so the Gini coefficient would be

one. Real economies have some, but not complete inequality, so the Gini coefficients for real

economic systems are between zero and one.

The Lorenz curve passes all the axiom of inequality. Any other measure of inequality that

has these properties is said to be Lorenz consistent. The properties are Reflexivity,

Transitivity, Anonymity, income homogeneity, Population independent and Pigou-Dalton.

Any other measure that is not consistent with Lorenz curve will give different result. Thus,

an inequality measure I (.) is Lorenz consistent if

Whenever one Lorenz curve I(x) dominates another I(y), then I(x) > I(y)

Whenever two Lorenz curve coincide say I(x) = I(y)

An inequality measure is weakly Lorenz consistent if

39

Whenever one Lorenz curve I(x) dominate another I(y), then I(x) ≥ I(y).

Whenever two Lorenz curve coincide, then I(x) = I(y)

An inequality measure is Lorenz inconsistent, when one Lorenz curve dominate another, then

I(x) < I(y).

The Gini coefficient

The Gini coefficient is a measure of inequality developed by the Italian statistician

Corrado Gini and published in his 1912 paper "Variabilità e mutabilità". The Gini coefficient

is widely used as a measure of income inequality, and there have been many attempts to find

an intuitive meaning to it. To mention a few examples, Yitzhaki (1979), Hey and Lambert

(1980) and Berrebi and Silber (1985) showed that the Gini coefficient represents the degree

of relative deprivation in a society, Lerman and Yitzhaki (1984) and Shalit (1985) related the

Gini coefficient to the covariance between a household's income and its income rank, and

Milanovic (1994) expressed the Gini coefficient as the weighted average of differences

between each household's importance as a member of a society and its importance as an

income-receiving unit. The Gini coefficient is a numerical measure of inequality based on the

Lorenz curve. These measures can be used to represent any sort of distributional inequity. It

is usually used to measure income inequality, but can be used to measure any form of uneven

distribution. The Gini coefficient is a number between 0 and 1, where 0 corresponds with

perfect equality (where everyone has the same income) and 1 corresponds with perfect

inequality (where one person has all the income, and everyone else has zero income). The

Gini index is the Gini coefficient expressed in percentage form, and is equal to the Gini

coefficient multiplied by 100.

40

Table 3.1: Gini Ratio From Various Studies

1960 1963 1965 1970 2005

Adelman and

Morris

0.45

Vielrose 0.474

Aboyade 0.5-0.6

Vielrose 0.492

Olaniyan and

Owoyemi

0.54

Source: Olaniyan & Owoyemi (2005)

World Bank (2003) shows that in 1996/97, Gini index for Nigeria was 0.506.

Table 3.1 presents some of the earlier estimates of inequality in Nigeria using Gini ratio.

We observed that inequality was low in the early 1960s, increased in 1965 and drop little in

1970 and again increased in 2005. The lowest inequality observed from the table is in 1960

when the Gini coefficient is 0.45 and the highest was in 1965 when the Gini Coefficient was

between 0.5-0.6 and also in 2005 with the Gini Coefficient of 0.54.

3.3: EMPIRICAL LITERATURE

During the past 20 years, there has been a tremendous focus on achieving growth in

developing countries in an effort to reduce poverty and boost living standards. For

policymakers around the world this is their top priority. Economists tend to advise them that

disciplined macroeconomic policies, structural policies that promote competition and

41

flexibility and strong institutions provide a framework in which entrepreneurship and growth

should flourish and according to Ricardo H., D. Rodrik and A. Velasco (2005) many

countries have adopted the policies known as Washington Consensus, that is the enforcement

of property rights, maintenance of macroeconomic stability, integration with the world

economy, and creation of a sound business environment, to help them achieve this goal.

Results have been extraordinarily varied, according to their findings that policies that work

wonders in one place may have weak, unintended or negative effects in other places. Roberto

Zagha, Gobind nankani and Indermit Gill, (2005) also found that the most important lesson

from this period is that our knowledge of economic growth is extremely incomplete. Ricardo

H., D. Rodrik and A. Velasco (2005) proposed that, countries need to figure out the one or

two most binding constraints on their economies and then focus on lifting them.

One study on income distribution and growth based upon both endogenous growth and a

new approach to reform that is much more contingent on the economic environment

endogenous policy theories was done by Perotti (1992). He applied an overlapping-

generations model to describe economic structure where growth is the result of private

investment in education and there is no capital market. He explained the political mechanism

by an endogenous median voter process that reveals individual preferences toward

distribution in the form of higher taxes. So, the lower the pretax income on the median voter

relative to the average, the higher her or his preferred tax rate, and, consequently, her or his

share of government expenditure in the GDP.

Using data from over 100 countries, Dollar and Kraay (2002) reject the trickle-down

approach to poverty reduction. They find that the per capita income of the poorest quintile of

the population grew one-for-one with the growth rate of the whole economy over the last four

decades; leaving the income distribution unchanged. Some studies in Nigeria have argued to

42

the contrary, that the poor has benefited more from these macroeconomic policies (Obadan,

1994; Faruquee, 1994; Canagarajah, et al., 1997). But Aigbokhan (2000) found that there was

positive real growth throughout the period of his study, 1980 to 1997, yet poverty and

inequality still worsened. However, other authors, Li and Zou, (1998), Barro, (2000) and

Lundberg and Squire, (2003), have found that greater inequality may promote economic

growth. The principal implications of their findings are that growth is good for poverty

reduction, irrespective of the nature of economic growth, and that pro-poor growth policies

are the best poverty reduction strategy.

Sami Bibi (2006) found that economic growth has led to a two-edge impact on poverty:

increasing mean income of the poor and reducing income inequality; thus reducing both

distributional-insensitive and distributional sensitive poverty indices when he used household

surveys from Mexico and Tunisia. According to him, for policy makers concerned with

poverty reduction, the aim should certainly be to sustain high growth, but with the poorest

capturing a proportionately larger share of the increment to growth. It is obvious that any

improvement in distribution achieved at the expense of growth would have adverse

implications for poverty reduction. Thus, there is no need for governments to implement

specific strategies to achieve the MDGs. They should instead maximise sustainable economic

growth by promoting competitive markets and adopting rigorous monetary and fiscal

policies.

Fosu(2008) study that explored the extent to which inequality influences the impact of

growth on poverty reduction, based on a global sample of 1977–2004 unbalanced panel data

for SSA and non-SSA countries. Several models are estimated with growths of the

headcount, gap, and squared gap poverty ratios as respective dependent variables, and

growths of the Gini and PPP-adjusted incomes as explanatory variables, the paper finds the

43

impact of GDP growth on poverty reduction as a decreasing function of initial inequality. The

study additionally observes that higher rates of increases in inequality tend to exacerbate

poverty, with the magnitude of this effect rising with initial income. The income–growth

elasticity, moreover, tends to increase with mean income relative to the poverty line. The

above estimated impacts are similar between the SSA and non-SSA samples with respect to

direction, so that within either sample there are considerable disparities in terms of the

responsiveness of poverty to changes in growth and inequality. This finding suggests that the

marginal benefit in terms of poverty reduction in the SSA region would require larger

reductions in inequality or accelerations in growth than elsewhere in the developing world.

Furthermore, the findings of the study suggest that the growth impact is likely to differ by

country in SSA, depending primarily on the inequality attributes of countries. For example,

the poverty-reduction efficacy of a given rate of growth acceleration in Ethiopia would be

more than twice that in Namibia, thanks to the much higher level of inequality in the latter

country. Similarly, the degree of responsiveness of Botswana‘s poverty rate is estimated to be

only slightly higher than that in Namibia, which might explain the minimal rate of poverty

reduction in Botswana, with the headcount poverty rate for instance falling by only 5

percentage points in a decade, despite the tremendous growth in that country. In contrast, in

Ghana where the income–growth elasticity is about twice that of Namibia, the headcount

poverty rate for example declined substantially, by about 10 percentage points within a

decade, in spite of the relatively modest growth. Thus, understanding the inequality-

generating characteristics of individual countries could help in designing most effective

poverty-reducing strategies for this region of the world where the challenge seems so great.

Meanwhile, a number of studies find that inequality plays an important role in the

income–growth–poverty relationship (e.g., Adams 2004; Kalwij and Verschoor 2007;

44

Ravallion 1997). Thus, meeting the poverty targets of the MDGs, for instance, may require

special attention predicated on a better understanding of the poverty–growth–inequality

relationship, particularly in SSA. Based on cross-country African data, Ali and Thorbecke

(2000) find that poverty responds more to income distribution than to growth. More recent

studies have focused on the role of initial inequality in the impact of growth on poverty. For

example, Ravallion (1997) and Easterly (2000) estimate the income–growth elasticity of

poverty as a decreasing function of inequality. Similarly, using the rather limited sample of

32 paired rural and urban sectors for 16 SSA countries employed in Ali and Thorbecke

(2000), Fosu (2008) arrives at a similar conclusion about the inequality impact on the income

elasticity of poverty. Adams (2004) also finds that a sub-sample of countries with a higher

level of inequality exhibits a smaller growth elasticity of poverty, on the assumption of a

lognormal distribution of income.

Bourguignon (2003) and Epaulard (2003) estimate equations that assume that the

income–growth elasticity, for instance, depends on the ratio of the poverty line to mean

income as well as on initial inequality. Based on similar specifications as in Bourguignon

(2003), Kalwij and Verschoor (2007) reach similar conclusions as in Bourguignon (2003) and

Epaulard (2003), and emphasize regional diversity in poverty responsiveness to growth and

inequality.

Adams (2004) used a new data set of 126 intervals from 60 developing countries to

analyze the growth elasticity of poverty and found that economic growth does indeed reduce

poverty (as measured by the international standard of $1.00/person/ day), the actual extent of

poverty reduction depends very much on how economic growth is defined. When economic

growth is measured by changes in survey mean income (consumption), there is a strong,

negative, statistical link between growth and poverty; however, when economic growth is

45

measured by changes in GDP per capita, the statistical relationship between growth and

poverty reduction is much weaker. However measured, economic growth reduces poverty in

this study because growth has little impact on income inequality. Income distributions do not

generally change much over time. Analysis of the 126 intervals included in the data set shows

that income inequality rises on average less than 1.0% per year. Moreover, econometric

analysis shows that economic growth—as measured by changes in the survey mean or GDP

per capita— has no statistical effect on income distribution. Since income distributions are

relatively stable over time, economic growth has the general effect of raising incomes for all

members of society, including the poor. In many developing countries poverty, as measured

by the $1 per person per day standard, tends to be ‗‗shallow‘‘ in the sense that many people

are clustered right below (and above) the poverty line. Thus, even a modest rate of economic

growth has the effect of ‗‗lifting‘‘ people out of poverty. Poor people are capable of using

economic growth—especially labor-intensive economic growth which provides more jobs—

to ‗‗work‘‘ themselves out of poverty. As noted above, however, the number of poor people

who are able to use economic growth to ‗‗work‘‘ themselves out of poverty depends very

much on how economic growth is defined. Adams (2004) further noted that the growth

elasticity of poverty is higher—not lower—when growth is defined using survey mean

figures as opposed to those coming from national accounts (the source of GDP per capita

data).

46

CHAPTER FOUR

METHODOLOGY

4.1: INTRODUCTION

This chapter clearly states the methods, techniques and approaches adopted in this

research. It further specifies the conditionality of the model and the sources of data used. In

order to achieve the objective of this study, we proceed by first identifying the unit of

analysis and then determining the definition of welfare.

In defining the unit of analysis, the we consider household as against individual members

of the household. This is dictated by the data we have on our disposal. Our unit of analysis is

thus the household and the extent of inequality is that between households. There are many

indicators of welfare that can be used as the basis for measuring inequality. The most

common ones are the income and the expenditure of the households. However, it has been

argued that income is problematic in the sense that the reported household incomes do not

always reflect the true position of household welfare. In this vein, this study uses household

per capita expenditure as the measure of welfare on which inequality index is computed.

The method adopted in this study is the Gini coefficient. The choice of this method is

made because it is best suited for calculating inequality. The Gini coefficient is one of the

commonly used measures of a welfare improvement indicator while the Lorenz curve is used

to measure changes in the income distribution.

47

4.2: MODEL DEFINITIONS

The Gini coefficient is widely used as a measure of income inequality, and there have been many

attempts to find an intuitive meaning to it according to Cheong (1999). To mention a few examples,

Yitzhaki (1979), Hey and Lambert (1980) and Berrebi and Silber (1985) showed that the Gini

coefficient represents the degree of relative deprivation in a society, Lerman and Yitzhaki (1984) and

Shalit (1985) related the Gini coefficient to the covariance between a household's income and its

income rank, and Milanovic (1994) expressed the Gini coefficient as the weighted average of

differences between each household's importance as a member of a society and its importance as an

income-receiving unit. The Gini coefficient is a numerical measure of inequality based on the Lorenz

curve. These measures can be used to represent any sort of distributional inequity. It is usually used to

measure income inequality, but can be used to measure any form of uneven distribution. The Gini

coefficient is a number between 0 and 1, 0 corresponds with perfect equality (where everyone has the

same income) where the Lorenz curve coincides with the 45 degree straight line and 1 corresponds

with perfect inequality (where one person has all the income, and everyone else has zero income). The

Gini index is the Gini coefficient expressed in percentage form, and is equal to the Gini coefficient

multiplied by 100.

Lorenz curve is an important tool for the analysis of inequality in a variety of situations –

inequality in the distribution of income within a population and many others. It is a graphical device

used to represent distributional inequality. When all the members of the population receive the same

income, the Lorenz curve is equi-distribution or identity function. The Lorenz curve bends downward

to the right, as the distribution of income becomes more unequal as illustrated below;

48

For a perfectly equal distribution, there would be no area between the 45 degree line and

the Lorenz curve -- a Gini coefficient of zero. For complete inequality, in which only one

person has all the income (if that were possible) the Lorenz curve would coincide with the

straight lines at the lower and right boundaries of the curve, so the Gini coefficient would be

one. Real economies have some, but not complete inequality, so the Gini coefficients for real

economic systems are between zero and one. The Lorenz curve illustrates the cumulative

income share on the vertical axis against the cumulative share of population on the horizontal

axis as in the figure above. If each individual had the same income, the income distribution

curve would be a straight line and the more bowed downward the Lorenz curve is, the more

unequal is the distribution of income in the graph.

4.3: TECHNIQUES OF EVALUATION

There are many ways to express and calculate the Gini coefficient according to

Milanovic (1997). Following the formula derived in Pyatt et al. (1980)), and used more

recently by Lerman and Yitzhaki (1984) and Yitzhaki (1994)) which will be adopted in work

is:

49

xN

rxarG

xi ),(cov2

…………………………………… (1)

Where covar (xi, rx) is the covariance between income (x) and ranks of all individuals"

according to their income (rx) ranging from the poorest individual (rank= I) to the richest

(rank=N).

N is total number of individuals or observation, and

x = mean income.

The Gini coefficient can also be calculated as the ratio of the area between the Lorenz Curve and the Equality line (or the 45 degree line) to the area below the equality line.

BA

AG

………………………………………………………… (2)

If A = 0, the Gini coefficient becomes 0 which means perfect equality whereas if B = 0,

the Gini coefficient becomes 1 which means completed inequality.

It is important to note, however, that the Gini coefficient represent less information than the

full Lorenz curve, different Lorenz curves may possess the same Gini coefficient but with

different interpretation. One would conclude, solely on the basis of two Lorenz curves having

the same Gini coefficients, that the two income distribution are equally unequal, whereas, one

Lorenz curve may show relatively more equal distribution among the low-income households

while the other Lorenz curve shows a relatively more equal distribution among the high-

income households. That is why it is important to augment the Gini coefficient with Lorenz

curve in its interpretation.

50

It is also important to note, however, that when the figure of the Gini Coefficient is high,

that is close to one, it means that income inequality is high and further depict that few

individuals are benefiting from the Economic growth and low Gini Coefficient means less

income inequality which further depict that majority of the individuals are benefiting from

Economic growth.

4.4: MODEL DERIVATIONS

Using equation (1), Gini coefficient can be state as:

xN

rxarG

xi ),(cov2

From equation (1) above;

covar(xi, rx,) = σxσrxp(x, rx,)……………………………………………………….(3)

Where σx = standard deviation of income,

σrx=standard deviation of individuals' ranks, and

p(x,rx) = correlation coefficient between x and rx.

Now, writing out the standard deviation of ranks

51

N

ii

rx

Ni

N 2

12

1

…………………………………. (4)

After some straightforward but tedious manipulation,

N

ii

Ni

2

12

=

N

ii

NNii

4

1)1(

22

=

=

N

ii

N

i

N

iNiNi

1 1

22 )1(4

1)1(

= 426

)1()1()12)(1(22

NNNNNNN

= 12

)1(3)12)(1(22

NNNNN

= 12

3632642323

NNNNNN

= 12

3

NN =

12

)1(2

NN,

Replacing the last expression into (4):

σrx=12

12N ……………………………………………………………………(5)

Using equation (5), we can write:

52

G = xN

rxar x),(cov2

G=

xN

rx x

12

),( 1N2 2x

G=NN

r x

x xx

1),(

3

12

………………………………………………………………(6)

For a sufficiently large N, the last term in (6) will be equal to 1. We thus obtain the final

formula for the Gini coefficient:

G = ),(3

1r x

x xx

This clearly shows that the Gini coefficient is the product of

(i) A constant,

(ii) Coefficient of variation of income, and

(iii) Correlation coefficient between income and rank.

4.5: SOURCES OF DATA

Data collection will essentially be from secondary source. The data for the study will be

collected from the Nigeria living Standard Survey (NLSS) 2004 of the National Bureau of

Statistics in collaboration with the European Union (EU), World Bank, United Nations (UN),

53

Department for international Development (DFID) and the UNDP in November, 2004. The

survey covered all the States of the federation and the Federal Capital Territory (FCT),

Abuja.

CHAPTER FIVE

ANALYSIS OF RESULTS

5.1: Introduction

Inequality in this paper is conceptualised as the dispersion of the distribution of the

attributes of the welfare indicators of the population, like income and consumption. As

revealed in the last chapter our welfare indicator is per capita expenditure of the household.

The results of the inequality using Gini Coefficient and Mean status of the household as well

as the decomposition analysis are presented in this chapter. Total inequality is decomposed

into within group components according to several socio-economic variables taken at a time.

The variables include the age, gender, and education of the head of the household. Others are

the economic activity of the household head, household size, rural, urban as well as the states

and geopolitical zone that the household head belongs.

5.2: Analyses of Results

The estimation results using Gini Coefficient and Mean is presented in table 5.1 below

Table 5.1: Estimation result

Areas

Analyzed

Percentage Share of

Households

Mean Gini

General 33795.37 0.44068

54

Rural 27.6 44626.98 0.44436

Urban 72.4 30928.02 0.43016

Source: Computed by the Author

We start by presenting the context of rural inequality in Nigeria in relation to urban and

national inequality. While, the mean per capita expenditure of households in the rural areas is

N44626.98 compared to N30928.02 among urban households. Although inequality among

urban households as reflected by the Gini index of 0.430 is very high, it is lower than both

rural and national inequality index. While the Gini index for the rural households is 0.444, it

is 0.441 among all household both urban and rural. Generally, all inequality indices reveal

that inequality is higher among urban households than rural households but the case is

different here because of the data in our disposal, because the observed household are not

equal, while 4010 households were observed in the rural area as compare to 15148

households observed in urban area respectively. The differential inequality reveals that since

most of the rural households are poorer, their per capita expenditure is dispersed compared to

what obtains among urban households. However, it is important to investigate the prevalence

of inequality among rural households as this will inform policy options of alleviating poverty

in the sector without worsening the inequality in the sector of the economy.

World Bank (2003) shows that in 1996/97, Gini Coefficient for Nigeria was 0.506. And

from our result presented in Table 5.1 above, we observed that the general Gini Coefficient is

0.441. This shows that there is a reduction in inequality in Nigeria from what we have in

Table 3.1 in literature review to 0.441. This significant reduction could be attributed to the

effort of government to reduce poverty in Nigeria through poverty alleviation programmes.

Nigeria is a federation with three tiers of governance at the national, state and the local

government levels. There are 36 states and 774 local governments in the country. However,

55

for geographical and tribal conveniences, the nation is often is subdivided into six

geopolitical zones. We therefore assess the impact of geopolitical zones on aggregate living

standards, as well as welfare differences between households. We find that location and

climate could have large effects on income levels and income distribution, through their

effects on transport costs, disease burdens, and agricultural productivity, among other

channels.

Table 5.2: Percentage share and Mean Expenditure of Households by

Geopolitical Zone

Areas

Analyzed

Percentage Share

of households

Mean Gini

General 33795.37 0.44068

South South 20.8 46649.26 0.392

South East 20.1 48256.52 0.3864

South West 20.5 43394.63 0.4024

North Central 14.1 26264.64 0.4524

North East 11.8 23711.36 0.3973

North West 12.7 21558.88 0.3870

Total 100

Source: Computed by the Author

Table 5.2 shows that South East zone has the highest mean expenditure of N48256.52

with 20.1 percentage share of the Households expenditure while North West zone accounts

for the least mean expenditure of N21558.88 with 12.7 percentage share of the households

expenditure. However, in spite of differential value of average expenditure across these

zones, the inequality index is high in all the geopolitical zones with the North central being

56

the zone with the highest level of inequality and the South East with the lowest level of

inequality. This means that some policies to reduce inter-geopolitical zones might reduce

some inequality in the country.

Table 5.3: Percentage share, Mean Expenditure Gini Coefficient of

Households by State

States Mean Sum Percentage

proportion of HH

expenditure

Gini

Abia 53235.62 30557246.65 4.72 0.361

Adamawa 23181.56 11706685.67 1.81 0.398

Akwa Ibom 44264.035 22574657.68 3.49 0.372

Anambra 55890.173 28448097.97 4.40 0.342

Bauchi 20537.247 11767842.44 1.82 0.441

Bayelsa 57480.017 30119528.62 4.65 0.351

Benue 37519.452 19435076.06 3 0.443

Borno 28606.511 14532107.59 2.25 0.367

Cross River 41825.09 20954367.35 3.24 0.419

Delta 36730.14 15279739.39 2.36 0.339

Ebonyi 33762.38 19210794.69 2.97 0.360

Edo 47057.15 26163774.09 4.04 0.411

Ekiti 41034.11 19655336.57 3.04 0.350

Enugu 43617.79 23553604.23 3.64 0.372

Gombe 22010.39 10873131.02 1.68 0.371

Imo 56194.23 28378084.98 4.38 0.427

Jigawa 12292.53 6871522.05 1.06 0.325

Kaduna 33101.44 18934024.38 2.92 0.384

Kano 27571.21 16101584.26 2.49 0.394

Katsina 23540.98 12688589.48 1.96 0.382

Kebbi 16621.14 8825826.88 1.36 0.284

Kogi 15526.96 9207489.12 1.42 0.460

Kwara 15862.74 8883136.01 0.14 0.463

Lagos 37941.90 18325936.89 2.83 0.488

Nassarawa 28377.88 13820018.54 2.14 0.362

Niger 27681.35 15418512.86 2.38 0.383

Ogun 50751.79 26796947.25 4.14 0.406

Ondo 38012.69 19994673.15 3.09 0.342

Osun 44700.42 23735925.24 3.67 0.358

Oyo 47365.66 24061755.33 3.72 0.328

Plateau 27175.21 13669128.98 2.11 0.394

Rivers 51456.72 19605008.79 3.03 0.400

57

Sokoto 18330.60 8542061.14 1.32 0.325

Taraba 29943.31 16319103.38 2.52 0.372

Yobe 18691.74 11009433.39 1.70 0.352

Zamfara 18302.50 10542236.94 1.63 0.326

FCT 42041.66 10888788.9 1.68 0.432

Source: Computed by the Author

58

Fig 2

59

Fig 3

lx

Table 5.3 shows the analysis of state inequality decomposition in Nigeria. We observed

average Household per capita expenditure of the Country was estimated to be 33795.37. State

average with highest figure was Bayelsa with 57480.017 as the mean expenditure and has the

highest percentage proportion of per capita expenditure of 4.65%. We further observed Jigawa to

have the lowest mean of 12292.53 and also with low Gini coefficient of 0.325, although Kebbi

has the lowest Gini coefficient of 0.284 and also we observed Lagos with the highest inequality

of Gini coefficient of 0.488.

Although, the first ten States average with high figure were Bayelsa (57480.017), Imo

(56194.23), Anambra (55890.17), Abia (53235.62), Rivers (51456.72), Ogun (50751.79), Oyo

(47365.66), Edo (47057.15), Osun (44700.42) and Akwa Ibon (44264.035). And the last ten

State average with low figure are Jigawa (12292.53), Kogi (15526.96), Kwara (15862.74), Kebbi

(16621.14), Zamfara (18302.5), Sokoto (18330.6), Yobe (18691.74), Bauchi (20537.25), Gombe

(22010.39) and Adamawa (23181.56). The analysis further revealed the inequalities of the

Households in the different States of Nigeria. From the observation, the first ten States with high

inequality from their Gini Coefficient are Lagos (0.488), Kwara (0.463), Kogi (0.460), Benue

(0.443), Bauchi (0.441), FCT (0.432), Imo (0.427), Cross River (0.419), Edo (0.411) and Ogun

(0.406). And the last ten State with low inequality from their Gini Coefficient are Kebbi (0.284),

Jigawa (0.325), Sokoto (0.325), Zamfara (0.326), Oyo (0.328), Delta (0.339), Anambra (0.342),

Ondo (0.342), Ekiti (0.350) and Bayelsa (0.351). Then, our chart shows the percentage

contribution of each States with Kwara having the lowest percentage share of 0.14 percent while

Abia with the highest percentage share of 4.72 percent.

lxi

Table 5.4: Mean Expenditure, Percentage Share of Households and

Household Expenditure by Gender of Household Heads

Gender Percentage

Share of

Households

Mean

Expenditure

Percentage

Share of HH

Expenditure

Gini

Male 85 32056.4 81 0.443

Female 15 43981.8 19 0.399

Source: Computed by the Author

Fig 4

lxii

Table 5.4 reveals that 85 percent of households in Nigeria are headed by male while only 15

percent are headed by the female. However, the mean expenditure of female-headed households

is richer as their mean expenditure of 43981.8 is higher than the mean expenditure of male-

headed households with 32056.4.

However, inequality index is a little low no matter the gender of the household head as the

Gini Coefficient for both sexes is 0.441. This is further revealed in the decomposition analysis as

revealed by Table 5.4; which indicate that gender inequality is not a prominent factor in overall

expenditure inequality. However, the Gini index indices suggest higher inequality among male

headed households of 0.443 than female headed households of 0.399, but there is no much

significant. This means that elimination of gender inequality will not reduce total expenditure

inequality significantly. We further observed that 85 percent of the male Household head

controlled 81 percent of the nation‘s wealth from their expenditure and 15 percent of the female

Household head controlled just 17 percent of the Nation‘s wealth.

lxiii

Table 5.5: Mean Expenditure and Proportion of Households by Age of

Household Head

Age Group

Class (In

Years)

Percentage

Share of

Households

Mean

Expenditure

Percentage

Share of HH

Expenditure

Gini

0-4 0 0 0 0

5-9 0 0 0 0

10-14 0.01 0 0.002 0

15-19 0.23 48879.92 0.33 0.405

20-24 2.07 48880.78 3 0.414

25-29 6.57 43132.56 8.38 0.428

30-34 10.40 34404.33 10.60 0.431

35-39 12.18 31701.18 11.43 0.437

40-44 13.16 30849.97 12.01 0.453

45-49 12.67 29546.98 11.08 0.417

lxiv

50-54 11.75 30140.13 10.48 0.429

55-59 7.96 31089.22 7.32 0.419

60-64 8.45 34230.94 8.55 0.440

65-69 5.53 37236.77 6.10 0.439

70 and above 9.04 40178.81 10.74 0.463

Source: Computed by the Author

There is a close link between the age structure and the distribution of income among the

people, because the size and composition of personal incomes from work, property and transfer

vary during the lifecycle, as well as for the fact that individual experiences reflect the different

historical periods in which people live. And according to the Life-Cycle hypothesis, that

household income usually increases gradually with age of the household head until a certain age.

After reaching a peak, it starts to decline. This is however not the case for Nigeria. Rather there

is U shaped relationship between the age groups and mean expenditure with two spikes at age

below 24 years and age 70 years and above categories. Table 5.6 reveals that the relative mean

expenditure of age groups15-19 years, 20-24 years, 30-34 years, 60-64 years, 65-69 years and 70

years and above are above the average mean expenditure of all the households while the mean

expenditure of other age groups are less than the average national mean expenditure. Incidentally

age group 0-4 years, 5-9 years and 10-14 years have the zero mean per capita expenditure. The

age group between 15 -19 years, 20-24 years and 25-29 years which correspond to a period when

most of the household head are single and unmarried accounted for the high mean expenditure.

We further observed that Households within age group 30-59 years were in their primes and the

crisis negatively affected their income status as at the period of reference. Further, the age-group

lxv

corresponds to the period when most individuals in Nigeria start their own families and start

having children which further reduced the per-capita expenditure and the current economic crises

left so many youths unemployed.

Table 5.5 further revealed that inequality is high among the households whose household

head‘s age falls within the age groups with the highest mean expenditures. The Gini Coefficient

for the age group of 70 years and above has the highest figure of 0.463 and approximately 9

percent of the Households have 10.74 percent of per-capita expenditure while the age group with

the lowest inequality is 15 – 19 age group with a Gini Coefficient of 0.405 and though age group

of 0-4, 5-9 and 10-15 have zero inequality because of no observation.

Our decomposition reveals that the disparity between the age - group is not significant in

overall inequality. This means that age is not important determinant factors in explaining

inequality among the households.

Table 5.6: Mean Expenditure and Proportion of Households by Education of

Households Head

Education

Level

Percentage

Share of

Households

Mean

Expenditure

Percentage

Share of HH

Expenditure

Gini

No Education 46 27086.50 37 0.427

Elementary 1 30175.92 1 0.426

Primary 4 37820.64 4 0.410

lxvi

Secondary 34 39971.49 40 0.417

Tertiary 6 58159.89 11 0.441

Others 9 27109.13 7 0.408

Source: Computed by the Author

In most developing countries the level of education is low and Nigeria is not an exception.

Table 5.6 shows that 46 percent of the Household had no education, 1 percent had elementary, 4

percent had primary school, 34 percent had secondary education, 6 percent had tertiary education

while 9 percent had other education. Human capital theory suggests positive correlation between

educational level and job opportunities and capacity to earn high income. Hence, employment

opportunities tend to vary between individuals depending on the level of educational attainment.

This is because one‘s labour productivity is affected by the amount of knowledge, information

and skills acquired and education can be a major determinant of inequality.

Table 5.6 shows a positive relationship between educational attainment of the household head

and the per capita mean expenditure. We found that the higher the educational attainment of the

head of the household, the higher the mean expenditure of the household. Hence, mean

expenditure is 27086.50 for households whose head has no formal education as the lowest while

households whose head had tertiary education with mean expenditure of 58159.89 as the highest.

Our findings in Table 5.6 revealed that inequality is highest in the Households of those with

tertiary education with Gini Coefficient of 0.441 as the overall Gini Coefficient while Household

with primary school education with the lowest inequality with Gini Coefficient of 0.410.

lxvii

Decomposing this inequality, we observed that in addition to inequality within each

educational level of household heads, differences in educational level attained by the household

head also account for inequality among Nigerian households. The implication is that although,

household heads may have attained the same educational level, their incomes are largely

determined by their employment activities which further determine the structure of earnings

which cause differences in earnings and thus mean average expenditure in educational level

attained by the household head also account for inequality among Nigerian households.

Table 5.7: Mean Expenditure and Proportion of Households by Economic

Activity of Household Head

Occupational

level

Percentage

Share of

Households

Mean

Expenditure

Percentage Share

of HH

Expenditure

Gini

Students, Retired,

Unemployed or

Inactive

5.25 50916.16 7.90 0.470

Professional 6.38 46898.13 8.86 0.445

lxviii

and Technical

Administration 0.21 50651.05 0.31 0.507

Clerical 4.93 42481.93 6.19 0.427

Sales and

Related

10.20 42133.48 12.20 0.426

Services and

related

3.56 40143.79 4.22 0.423

Agricultural

and Forestry

61.97 27787.29 50.96 0.418

Production and

Transport

2.51 41015.76 3.04 0.407

Manufacturing

and Processing

1.53 38876.43 1.76 0.404

Others 3.47 39296.36 4.04 0.410

Source: Computed by the Author

It should be of interest to identify the degree to which differences in the type of primary

occupation contribute to overall income inequality and the role it has played in the widening of

income disparity. Table 5.7 shows that farming is still the main stay of employment in Nigeria.

61.97 percent of households in Nigeria engage in farming activities. Our results revealed that

mean expenditure for households that are Students, Retired, unemployed or inactive is 50916.16

as the highest Mean expenditure and agricultural and forestry activity with the lowest mean

expenditure of 27787.29. This suggest that farming activities bring low income, that even with

61.97 percent of the Households engaged in farming we still have low mean expenditure. The

decomposition of the inequality measures are illustrated in Table 5.7, which reveals

lxix

administration with the highest inequality of 0.507 as the Gini Coefficient while manufacturing

and processing has the lowest inequality of 0.404 as the Gini Coefficient.

Table 5.8: Mean Expenditure and Proportion of Households by Household

Size

HH size class Percentage

Share of

Households

Mean

Expenditure

Percentage

Share of HH

Expenditure

Gini

1 person 11.46 20268.35 23.83 0.376

2-4 persons 39.76 35718.44 42.02 0.393

5-9 persons 42.10 24246.14 30.21 0.391

10-19 persons 6.61 19997.41 3.91 0.453

20 persons

and above

0.06 14086.91 0.03 0.303

Source: Computed by the Author

It has been hypothesised that although larger households tend to have higher level of

expenditure, per capita household expenditure decreases as the household size decreases. This is

not entirely true of the Nigerian case. The mean expenditure of the household with 2-4 persons

household size is the highest as observed from table 5.8 while mean expenditure of the

household with 20 persons and above is smallest. We further observed that household size of 5-9

persons is more common, being 42.10 percent of the total household observed.

Table 4.8 presents the inequality decomposition by household size and finds that Inequality is

highest within 10-19 persons households with the Gini Coefficient of 0.453 and lowest within

lxx

20-persons and above households size with a Gini Coefficient of 0.303. In other words, making

household size equal will not have significant bearing on the overall inequality in Nigeria.

Table 5.9: Mean Expenditure and Percentage Share of Households

Component Expenditure

Components of HH

Expenditure

Mean Expenditure Percentage share of

Expenditure

Food 48163.47 37

Own Produced 22412.13 17

Education 6883.55 5

Health 17874.85 14

Rent 10682.47 8

Non Food Frequent 13618.69 11

Non Food Infrequent 10481.07 8

Source: Computed by the Author

We observed in table 5.9 the components of Households expenditure and found that the bulk

of Household expenditure goes for food with the highest mean expenditure and 37 percent share

of total expenditure. Education has the lowest mean expenditure with 5 percent share of the total

expenditure, this suggest a great implication on the human capital development in Nigeria. Table

5.9 was better buttress with the help of pie chart above.

lxxi

Fig 5

Table 5.10: Cumulative Relative Frequencies of Households per Capita

Expenditure and Households

Per Capita

Expenditure

Percentage

Share of

Households

Cumulative

share of

Households

Deciles share

of

Cumulative

share of

lxxii

Class (N)

Expenditure Expenditure Households Households

Under 10000 2.73 2.73 1.31 1.31

10001-20000 12.48 15.21 2.83 4.14

20001-30000 14.85 30.06 2.03 6.17

30001-40000 12.60 42.66 1.23 7.4

40001-50000 10.65 53.31 0.81 8.21

50001-60000 8.24 61.55 0.51 8.72

60001-70000 7.085 68.635 0.37 9.09

70001-80000 5.410 74.045 0.24 9.33

80001-90000 4.148 78.193 0.17 9.5

90001-100000 3.421 81.614 0.123 9.623

100001-110000 2.329 83.943 0.075 9.698

110001-120000 2.345 86.288 0.069 9.767

120001-130000 1.656 87.944 0.045 9.812

130001-140000 1.479 89.423 0.037 9.849

140001-150000 1.160 90.583 0.028 9.877

150001-160000 1.027 91.61 0.023 9.9

160001-170000 0.920 92.53 0.018 9.918

170001-180000 0.542 93.072 0.011 9.929

180000-190000 0.569 93.641 0.010 9.939

lxxiii

190001-200000 0.572 94.213 0.010 9.949

200001-210000 0.472 94.685 0.008 9.957

210001-220000 0.363 95.048 0.006 9.963

220001-230000 0.208 95.256 0.003 9.966

230001-240000 0.438 95.694 0.006 9.972

240001-250000 0.076 95.77 0.001 9.973

250001-260000 0.274 96.044 0.004 9.977

260001-270000 0.124 96.168 0.002 9.979

270001-280000 0.298 96.466 0.004 9.983

280001-290000 0.264 96.73 0.003 9.986

290001-300000 0.046 96.776 0 9.986

300001-310000 0.057 96.833 0 9.986

310001-320000 0.293 97.126 0.003 9.989

320001-330000 0.050 97.176 0 9.989

330001-340000 0.361 97.537 0.004 9.993

340001-350000 0 97.537 0 9.993

350001-360000 0.054 97.591 0 9.993

360001-370000 0.113 97.704 0.001 9.994

370001-380000 0 97.704 0 9.994

380001-390000 0.059 97.763 0 9.994

lxxiv

390001-400000 0.061 97.824 0 9.994

400001-410000 0 97.824 0 9.994

410001-420000 0.127 97.951 0.001 9.995

420001-430000 0.131 98.082 0.001 9.996

430001-440000 0 98.082 0 9.996

440001-450000 0.069 98.151 0 9.996

450001-460000 0 98.151 0 9.996

460001-470000 0,217 98.368 0.002 9.998

470001-480000 0 98368 0 9.998

480001-490000 0.075 98.443 0 9.998

490001-500000 0.077 98.52 0 9.998

500001-510000 0.078 98.598 0 9.998

510001-530000 0 98.598 0 9.998

530001-540000 0.083 98.681 0 9.998

540001-660000 0 98.681 0 9.998

660001-670000 0.103 98.784 0 9.998

670001-970000 0 98.784 0 9.998

970001-980000 0.150 98.934 0 9.998

980001-1010000 0 98.934 0 9.998

1010001-1020000 0.157 99.091 0 9.998

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1020000-1730000 0 99.091 0 9.998

1730001-1740000 0.268 99.359 0 9.998

1740001-1940000 0 99.359 0 9.998

1940001-1950000 0.301 99.66 0 9.998

1950001-2290000 0 99.66 0 10

2290001-2300000 0.355 100 0 10

Source: Computed by the Author

Table 5.10 show the per capita expenditure distribution of the households. It can be shown in

the above that 82.05 percent of the households controlled 53.30 percent of the total expenditure

lxxvi

earned less that N50000 annually while the remaining 17.95 percent of the households controlled

46.7 percent of the total expenditure which means that quarter of the total of the household

controlled almost half of the wealth of the Nation. This shows that the distribution of wealth is

not fairly equal in the Country. This is confirmed by the Gini coefficient of 0.441. According to

the ratio got from Gini coefficient, the disparity in the distribution of wealth was not great but it

is quite obvious that it exists. For there is not to be any disparity in the distribution of wealth,

that is, perfectly distributed, the Gini index should be zero. Therefore, what we have is high

enough to cause some problems.

CHAPTER SIX

SUMMARY, RECOMMENDATION AND CONCLUSION

6.1: Summary

Increasing income inequality and poverty continue to be the most challenging economic

problem facing most developing countries. This study attempted to investigate the distributional

trend of income in Nigeria and examine the issue of inequality in expenditure among households

as well as urban-rural difference in consumption among households and further examine

geopolitical zone inequality in Nigeria. That is, the decomposition analysis was divided into two

categories. The first category is concerned with the decomposition of households‘ expenditure.

This underscores the contributions of these components to overall inequality and may help in the

design of effective economic and social policies to reduce inequality and poverty in Nigeria. The

second category of decomposition analysis dealt with the breakdown of expenditure into

population sub-groups (This approach starts with the division of a sample into discrete

categories; for instance, rural and urban residents, gender, age group, education level of

household heads, household size, occupation, states and geopolitical zones), and then follows

with the calculation of the level of inequality using Gini coefficient. The results of our analysis

lxxvii

indicate that factors such as age, gender, and education level of the household head are important

factors in explaining inequality profile in the country. We however found that inequality exists in

the rural and urban areas but more of the rural areas and inequality is very high in some of the

geopolitical zones. This thus suggests policies that will alleviate poverty in the rural and urban

areas as well as policies to reduce inter geopolitical zone access to opportunities.

It has been reported that the scourge of poverty in Nigeria is tilted towards the rural sector.

Rural areas in Nigeria, according to the World Bank (1996), accounted for 66 per cent of the

incidence of poverty, 72 per cent of the depth of poverty and 69 per cent of the extreme poor.

Several studies have revealed that the majority of the rural dwellers are engaged in farming. We

also observed that inequality in the rural areas is higher than the urban areas, and even higher

than the general inequality.

Again, the gap between the rich and the poor in Nigeria continued to widen everyday and this

has created a serious threat to both the socio-economic and political stability in the country.

Meanwhile, this study has shown that consumption inequality is increasing in the rural and urban

areas and this can be linked to the growing dimensions of poverty.

In spite of the various economic reforms and policies of the government to eliminate

inequality and reduce poverty to the bearable state in the country, inequality still persists and

poverty keeps increasing everyday. One, therefore, is inclined to wonder if these policies are

actually implemented or are simply touted.

6.2: Recommendations

lxxviii

Based on the findings from the analysis carried out, an encompassing policy framework

would be necessary to reduce national inequality and poverty. Some of the policies might include

the following:

i. Agricultural activities should be promoted among rural households in Nigeria. This is

because, apart from being an inequality decreasing income source, it remains a major

income source for the rural households. Policy makers, therefore, must concentrate on

measures to increase agricultural productivity through targeted efforts such as

distribution of improved seed varieties and better extension services delivery. Despite

the concern that agricultural growth may not provide the exit way out of poverty, the

results of this paper seem to suggest that there is scope for poverty reduction through

growth in agricultural income.

ii. Direct targeting of the poor households for income transfer, should be considered to help

reduce the high level income inequality in rural Nigeria.

iii. There should be policies targeted in Redistribution of wealth.

iv. Measures should be taken by the government to pursue MDG‘s goals seriously and there

should be programs to track the Virtual Poverty Fund in MDG‘s office.

v. Measures should be taken to improve human development level in the country to energise

the real sector and also to develop social expenditure programs targeting the poor and

vulnerable communities in Nigeria.

vi. Government should intensify efforts towards the achievement of her poverty reduction

strategies; the realisation of the objectives of the NEEDS living document should

remain the paramount concern of the government.

lxxix

vii. Measures should be taken to design programme that are geared towards capacity building

for Nigerians so as to minimise the ugly trend of unemployable jobs seekers.

viii. Massive industrialisation of the rural areas should be embarked upon in order to develop

those areas and so stop the rural urban drift.

ix. There is need to intensify the crusade on population control since large households have

low per capita income.

x. The Government Poverty Alleviation Programme should be restructured if not re-

designed and should be centred on the ‗basic needs‘ approach. This approach

emphasizes the importance of separating generalized increase in income from the

more significant attainment of the requirements for a permanent reduction of poverty

through the provision of health services, education, housing sanitation, water supply

and adequate nutrition.

xi. Government value for money audit or due process mechanism in public procurement

should be intensify since government tackle corruption and improve transparency in

public expenditure through this.

xii. The two government commissions; Economic and Financial Crime Commission as well

as Independent Corrupt Practices Commission meant to tackle corruption in the

domestic business environment should intensify their effort in pursuing cases of

corrupt practices especially corruption in public offices.

6.3: Conclusion

Poverty has the consequence of breeding social disillusionment with respect to what the

societal objectives are and member‘s responsibilities towards attainment of these objectives. Just

lxxx

as ignorance maintains poverty, so also can poverty perpetuate ignorance, since the victims

cannot think and plan beyond where the next meal is coming from. Moreover, in a country or

locality where the concentration of the bulk of wealth is in few hands, there is serious

implication. A society where majority spend almost 90% of their income on consumption and

having little or nothing for saving, which could be ploughed back into the economy for re-

investment, economic growth would be slow and impeded, since the rate of economic growth is

a function of investment through multiplier effects. This means that the group of people affected

would not participate effectively in the process of development of that nation. In other words,

poverty is a vicious cycle reproducing itself in perpetuity. For the poor to back out of this vicious

cycle in which they are presently enmeshed, government must make reaching the poor a priority

in its own right.

Despite the commitments already shown by the government of the Country towards the

achievement of the goal of reducing inequality, it is crystal clear that Nigeria has had various

programs targeted at reducing inequality and poverty, either in consumption of income but the

problem has been in the implementation and sustenance of the programs.

Therefore, efforts to reduce poverty are unlikely to succeed in the long run unless there is

greater investment in the human capital of the poor. Improvement in education, health and

nutrition directly address the worst consequences of being poor. There is ample evidence that

investing in human capital, especially in education, shelter and social services increases the

poor‘s productivity and also attacks some of the most important causes of poverty. Improving the

social services of the poor will be an essential part of any long-term strategy for reducing poverty

in Nigeria as a whole.

lxxxi

Conclusively, any policy designed to ameliorate the plight of the poor must among other

things recognize housing, provision of potable water, improved health care facilities, improved

transportation in terms of good roads and provision of more mass transit buses and train, sound

education for the wards of the poor and employment opportunities. No societies can surely

flourish and be happy, when by far the greater part of the numbers are poor and miserable.

However, we would like to acknowledge that all government economic reforms would be

inadequate unless they are able to result in tangible improvements in the welfare of the ordinary

Nigerians. As Amartya Sen (okonjo-Iweala, 2006) once said, the goal of development must be

viewed as enhancing the capabilities of (poor) people. Therefore, the need to alleviate poverty in

Nigeria as a whole should be the highest priority of the government and the citizenry.

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