1. i
THE EFFECTS OF URBANIZATION ON AGRICULTURAL PRODUCTIVITY IN
WEST AFRICA (1989-2010)
MUYIWA-ONI OLUTOBI HARRY
(10AF010493)
BEING
A RESEARCH PROJECT SUBMITTED IN PARTIAL FULFILLMENT OF THE
REQUIREMENT FOR THE AWARD OF B.SC DEGREE IN ECONOMICS TO THE
DEPARTMENT OF ECONOMICS AND DEVELOPMENT STUDIES, SCHOOL OF
SOCIAL SCIENCES, COLLEGE OF DEVELOPMENT STUDIES, COVENANT
UNIVERSITY, CANAANLAND, OTA,
NIGERIA.
MARCH 2014

2. ii
CERTIFICATION
It is hereby certified that this research project, written by MUYIWA-ONI OLUTOBI HARRY,
was supervised by me and submitted to the Department of Economics and Development
Studies, School of Social Science, College of Development Studies, Covenant University, Ota.
Mrs. Oluyomi Ola-David ………………………………….
(Supervisor) Signature & Date
Dr. P. Alege …………………………………..
(Head of Department) Signature & Date

3. iii
DEDICATION
To all powerful and ever living God and also to my parents, Mr and Mrs R.A Muyiwa-Oni,
In memory of Ihuoma Ndubuisi, Onyeke Emmanuel, Kelechi Ndubuisi and Egemba Victor.

4. iv
ACKNOWLEDGEMENTS
My sincere gratitude goes to Almighty God who has been my help since the beginning of this
work till this point through divine inspiration .I owe the completion of this work to a lot of
individuals apart from myself, and I wish to acknowledge a few of these people here, who
contributed immensely.
The Chancellor, Dr David Oyedepo, who laid the great pathway that I currently walk in and
also for pursuing the vision of Covenant University, which I am truly a beneficiary. The Pro-
Chancellor, Pastor Abraham Ojeme. The Vice-Chancellor, Prof. C.K Ayo whose short and
snappy words have inspired me to greatness. The Registrar, Mr. Muyiwa Oludayo whose
communication skills I truly crave. The Dean, College of Development Studies, Prof. O.
Olurinola, The Head of Department, Economics and Development Studies, Dr. P. Alege whose
effective teaching methods have certainly made me a better student.
My deep and utmost gratitude goes to my supervisor Mrs. Oluyomi Ola-David who was there
from the beginning and helped me in many ways. God bless you Ma. I would also duly
acknowledge my Lecturers that taught me during the course of my study: Dr. M. Adewole, Dr.
H. Okodua, Dr. O. Ewetan, Dr. E. Urhie, Dr. E. Osabuohien, Dr. Oluwatoyin Matthew, Mr A.
Alejo, Mr John Odebiyi, Mr. Stephen Oluwatobi, Mr. Adeyemi Ogundipe, Mrs O. Ogundipe,
Mrs T. Amalu, Miss. Ibukun Beecroft, Miss O. Akinyemi.
My parents Mr. and Mrs. R.A Muyiwa-Oni, my siblings Soji, Femi, Solomon, Yemisi,
Akinwale, Olumide, Akinfolarin and Eniola for their moral and financial support. I also want
to thank my hospitality family, my special ones Segun Afolabi, Babajide Ajayi, Uzoma
Obinna, Babatunde Macaulay ,Soso, David Egwede, Ifeanyi, Jennifer Subi, Yadinma, Kome,

5. v
Faith, David Olaleye, Uyi, Femi, Jibola, Tominiyi, Jachike, my coursemates and my friends for
their help and also making my stay in Covenant University worthwhile , I cherish you all.

6. vi
TABLE OF CONTENTS
TITLE PAGE i
CERTIFICATION ii
DEDICATION iii
ACKNOWLEDGEMENTS iv
ABSTRACT x
CHAPTER ONE: INTRODUCTION
1.0 Background ofthe study 1.
1.1 Statement ofResearch Problem 5.
1.2 Research Questions 7.
1.3 Research Objectives 8.
1.4 ResearchHypotheses 8.
1.5 Scope of the study 9.
1.6 Justification of the study 9.
1.7 Structure of the study 9.
CHAPTER TWO: LITERATURE REVIEW
2.1 Introduction 11.

7. vii
2.2 Review ofDefinitional Issues 13.
2.3 ReviewofTheoretical Issues 16.
2.3.1 The Theory ofAgglomeration Economics 17.
2.3.2 The Lewis two sector model 20.
2.3.3 Todaro`s Rural-Urban Migration Theory 21.
2.3.4 The Harris-Todaro model on Migration 22.
2.3.5 Mabogunje`s Central Place Theory 24.
2.3.6 Ravenstien`s Laws ofMigration 25.
2.4 ReviewofMethodological and Empirical Issues 26.
2.5 Conclusion 34.
CHAPTER THREE :THEORETICAL FRAMEWORK AND RESEARCH METHODOLOGY
3.1 Introduction 35.
3.2 Theoretical Framework 35.
3.3 Research Methodology 37.
3.4 Model Specification 39.
3.5 Technique ofEstimation 41.
3.6 Justification ofVariables Used 42.
3.7 Apriori Expectation 43.

8. viii
3.8Data Employed, Measurement and Sources 44.
CHAPTER FOUR :DATAANALYSIS AND INTERPRETATION
4.1 Introduction 45.
4.2 Descriptive analysis 45.
4.3 Empirical Analysis 46.
4.3.1 Test for multicollinearity 46.
4.3.2 Test for heteroskedasticity 47.
4.3.3 Hausman test 48.
4.3.4 Interpreting the Random Effects Model 49.
4.3.5 Testing for Random Effects using the Breush-Pagan Lagrange Multiplier (LM) 52.
4.4 Summary of findings 53.
CHAPTER FIVE :SUMMARY, RECOMMENDATIONS ANDCONCLUSION
5.1 Summary 55.
5.2 Recommendations 56.
5.3 Conclusion 58.
5.3.1 Limitations ofthe study 58.
5.3.2 Suggestions for further study 59.
REFERENCES 60.

9. ix
APPENDICES 62

10. x
ABSTRACT
This study empirically examines the effects of urbanization on agricultural productivity in West
Africa using cross-sectional data from 1989-2010. The main objective of the study is to
examine the effect of urbanization on agricultural productivity. This research is divided into
five chapters, chapter one provides an introduction to the subject matter, chapter two looks at
the review of past literatures, chapter three explains the chosen theory and also the derivative
of its equation and also shows the model and methodology used in the study. In chapter four
various tests were run so as to establish the impact of the independent variables on the
dependent variable. The last chapter provides conclusions and required policy
recommendations based on the findings in previous chapter. The study employs panel data
analysis and the random effects model was used because it was most suitable for the research
after running the hausman test to ascertain whether time invariant variables and unique
errors are correlated with the regressors or not. In order to capture West Africa, a sample of
14 countries in the region was used. The study made use of the following variables in
capturing the effects of urbanization on agricultural productivity: agricultural productivity in
terms of labour productivity, urbanization level, life expectancy at birth, education level in
terms of primary school enrollment, industrial productivity and agricultural population.
Results show that urbanization significantly affects agricultural productivity in West Africa.
Another important result is that education level has a significant impact on agricultural
productivity.
Keywords: Urbanization, Agricultural productivity, urban agglomeration and panel data

11. 1
CHAPTER ONE
INTRODUCTION
1.0 Background of the study
Large share of the growth of population of the world in coming decades will be situated in the
cities of developing countries. Cities in sub-Saharan Africa will be responsible for a good
number of the increase in the demand for food. People who dwell in urban areas are not just
consumers but they are also producers of food items especially perishable agricultural produce
of high value (United Nations, 2000). West Africa is mainly characterized by developing
countries. Urban population growth experienced there is a product of both rural-urban
migration and growth of population that comes naturally. There is a form of pressure that rapid
stage of rural-urban migration puts in cities and rural areas. First is that it has impact on almost
all the dimensions of development in countries which can be in form of education,
transportation, supply of water, health and so on. Secondly, it is also responsible for the
absence of educated youths in rural areas which is called youth drain which affects agricultural
labour productivity and the social life of people in rural areas.
Bocquier projected that the proportion of the world population living in cities and towns in the
year 2030 would be approximately 50 percent greater which is significantly less than the 60
percent that was predicted by the United Nations (UN). This is so because of rapid
urbanization has been discovered to be disorderly thereby making urbanization unsustainable
(The futurist magazine, 2005 and Bocquier, 2005). Both the UN and Bocquier were of the
opinion that more people will flock into cities, but Bocquier believes that many people will
leave urban areas once they realize that there is no work for them and the problem of shelter.

12. 2
According to UN-habitat, sub-Saharan Africa is urbanizing faster than any other continent.
West Africa which is in Sub-Saharan Africa has only recently started its urban transition; the
pace is such that it can expect an urban majority by 2030. Djibouti, Gabon, Mauritania and
South Africa were the countries that had urban majorities in 2001. Amazingly it has been
forecasted by UN-habitat that not less than nine sub-Saharan countries will pass the 50 percent
urban mark at the end of this decade. Also in some countries in West Africa, urbanization rates
exceed 4 to 5 percent per annum. Amazingly these rates are close to rates experienced in
Western cities at the end of the 19th century. The average sub-Saharan Africa typically
experienced persistent annual urban growth rates of 5 to 6 percent, while some cities saw
annual growth rates in excess of 10 percent, which means that the population doubles every
decade. Johannesburg was the sole sub-Saharan African city that exceeds 1 million inhabitants
in 1960. Then in 1970 we had four Cape Town, Johannesburg, Kinshasa and Lagos. At the end
of 1989, the list included Abidjan, Accra, Addis-Ababa, Dakar, Dar es Salaam, Durban, East
Rand, Harare, Ibadan, Khatoum, Luanda and Nairobi.
Mabogunje (2002) described today`s Nigerian city to be characterized with substandard and
inadequate housing, lack of infrastructure, slums, poverty, low productivity, youthful
delinquency, crime, transportation problems and held urbanization as the root cause of all that
was stated earlier with pollution and environmental degradation. As at 2004, Nigeria was
ranked 151st on the Human development index, then in 2012 Nigeria was ranked 153rd on the
development index of 177 countries worldwide (UNDP, 2004, 2013)
In Ghana, Over 60 percent of the populations are involved in agriculture and it remains a major
source of employment to the people of Ghana. This deprives the sector of land but therefore it

13. 3
brings an increase in the unemployment rate. The dual pressure of rapid Urbanization and fast
growing population have wreaked havoc on agricultural land relations and land management in
Tamale(Ghana) thereby reducing productivity (Naab, Dinye and Kasanga, 2013). The chief
crisis of rapid urban growth is the problem of varying land use patterns.
Nigeria as a nation has been experiencing an accelerated shift in her population from rural to
urban areas. This is also visible in other countries in West Africa. In Nigeria the degree of
Urbanization has improved tremendously most especially in the past 25 years. The census that
was conducted in 1952 indicated that there were about 56 cities in the country and about 10.6
percent of the total population lived in these cities. Amazingly, this rose to about 19.1 percent
in 1963 and 24.5 percent in 1985. Nigeria is regarded as the most heavily populated nation in
Africa and also one of the fastest on the rise on earth. Nigeria is characterized with 250 ethnics
groups. The largest of these groups are the Hausa and Fulani who reside in the northern part of
the country. The economy of Nigeria historically was based on agriculture, and about 70
percent of the work force participates in it. Major crops produced are Cocoa, peanuts, palm oil,
corn, rice, sorghum, millet, soybeans, cassava, Yam and rubber. In addition, cattle, sheep,
goats, and pigs are raised.
Petroleum is the leading mineral produced in Nigeria and provides about 95 percent of foreign
exchange earnings and the majority of government revenues. Petroleum production on an
appreciable scale began in the late 1950s and by the early 1970s it was by far the leading
earner of foreign exchange. The growing of oil industry attracted many to urban centers, to the
detriment of the agricultural sector and the huge government revenues from oil led to
widespread corruption that has continued to be a problem. Amazingly in the 1980s a decline in

14. 4
world oil prices provoked the government to bolster the agricultural sector. It is essential to
note that both the refinery capacity and agriculture have not kept the pace with population
growth thereby forcing the nation to import refined petroleum products and most importantly
food items. In the historical perspective, Nigeria had long benefited from rapidly growing
export even before the discovery of petroleum in 1956. Between 1900 and 1929 the volume of
exports was dominated mainly by palm produce, groundnuts, cocoa, rubber and cotton grew at
an average annual rate of 5.5 percent.
Iwayemi (1995) mentioned that the agricultural sector of any economy is known to play many
key roles in the process of economic development. He opined that these roles can change with
stages of economic development. But in general, the roles often associated with agriculture in
the early phases of economic development include the generation of most of the gross domestic
product (GDP) , the provision of most of the employment opportunities for the labour force,
the provision of adequate food for a growing population, the generation of foreign exchange,
the generation of savings or investment in agriculture as well as other sectors, the production of
raw materials and the release of surplus or under-utilized resources for use in other sectors
especially in the fledging industrial sector and the provision of an expanding market for the
products of non-agricultural sectors. Most of these roles derive from the naturally domineering
position of agriculture in the early stages if economic development. The rest are the
consequences of growth and structural transformation over time in the economy.
Therefore, the leading role of the agricultural sector in the generation of gross domestic
product as well as employment opportunities is a basic feature of primordial market economies
which stems from low productivity, high degree of subsistence production and rapidly

15. 5
increasing population. It also stems from the lack of a clear line of specialization in economic
activities like agriculture. Comparing this with others it led to many of the activities associated
with non-agricultural sectors have to be carried out within the agricultural sector, In addition to
normal agricultural activities.
Urbanization can be defined as the increase in the percentage of the national population that is
urbanized (Henderson and Wang, 2004). According to Anthony (2011) Urbanization is the
process whereby large number of people congregate and settle in an area, eventually
developing social institutions such as government and businesses in order to support
themselves. Urbanization is as a result of bodily growth of urban areas caused by population
immigration to an existing urban area. In mentioning the effects of urbanization it is not
possible to overlook the increase in population density and most importantly increase in
administration services. Urbanization is attached to the growth of cities. United Nations (2007)
described urbanization is the movement of people from rural areas to urban areas with
population growth which equates urban migration. The problem of many countries is the
reason why the exact definition and population size of urbanized areas varies. Over the years
Farmers have through the application of science and technology, evolved methods of
increasing agricultural productivity (Ukeje, 2000). In Nigeria agricultural productivity has been
growing over the years at different rates. Ukeje divided the periods into three namely; pre-SAP
era (1970-1985), SAP era(1986-1993) and the era of guided deregulation(1994-1999).
1.1 Statement of Research Problem
The problems that cities in West Africa are facing have resulted largely because urbanization is
yet to correspond with the growth or decrease in agricultural productivity and output. This is

16. 6
responsible for the dwindling of the resources required to manage cities that has been
reoccurring since last two decades and also increase the productivity in agriculture.
Interestingly, there has been continued agglomeration of people into urban centers whose
population is on the increase. Is it possible for cities in West Africa to provide their dwellers
that are educated and in good health with the employment and income-earning opportunities
for them to be able to take care of their well being and welfare through increase in agricultural
productivity?
Growth in urban population goes with no equivalent growth in land supply. Also land is fixed
in supply and does not increase with increasing population growth. Agricultural lands are most
affected by rapid urbanization and its functions of demand. Land uses for residential, industry
and commercial, civic and culture tend to dominate agricultural lands in the bid for space in the
urban place. This is responsible for Farmers being underprivileged to have access to arable
land to cultivate thereby reducing agricultural productivity. Attainment of higher productivity
presupposes the availability of skilled labour force. Skilled labour force is required to
transform the static past into a dynamic present and prosperous future. The inadequacy of
skilled farm labour is further compounded by unavailability of labour, particularly when it is
required to satisfy seasonal labour demand. This labour shortage has been aggravated by a
substantial reduction in the supply of family labour due to the persistent rural-urban drift.
It has been observed that people in West Africa migrate to urban areas so as to attain better life
and they fail to return to rural areas when they are convinced that the dream of better life is not
true. This is so because of the rate of competition for getting job and other basic needs attached
to the urban center. It has also been projected that West Africa will soon experience swift

17. 7
urban population growth, and it is not certain that the region has the capacity to handle the
projected enormous increase. There is also no form of any theoretical consensus that will be
able to explain the workings of urban population growth and urbanization in West Africa.
Same theories are also contradicted due to the portrayal of the reality (Nordhag, 2012).
During the colonial era in Nigeria, at the time when industrialization was introduced in Lagos
and this resulted in development, since then the government shifted focus from rural areas
which could not welcome industrialization. Due to this even the government started allocating
more funds and resources to the urban areas thereby leaving the rural areas to remain
undeveloped and static. This is the responsible for the poor welfare of the major percentage of
the population of the country who still reside in the rural area with only localized farming and
trading.
Urban areas development due to industrialization has led to the migration of people from the
rural areas to urban areas. Majority of the people that migrate to urban centers without any
form of education or skills are responsible for over-population experienced in urban centers in
sub-Saharan Africa and also end up as nuisance retarding the development of urban areas.
Same over-population in urban areas welcomes poor welfare.
1.2 Research Questions
Based on the justification of this study to every economy, this study attempts to answer the
following questions:
i. To what extent is the impact of urbanization on agricultural productivity in West
Africa?

18. 8
ii. What measures can be implemented to control urbanization in West Africa?
iii. Is there a possibility that the current rate of urbanization can be a mechanism of
economic development through increase in agricultural productivity?
1.3 Research Objectives
The main objective of this study is to examine the effect of urbanization on agricultural
productivity in West Africa. The specific objectives are;
i. To ascertain the extent of the impact of urbanization on agricultural productivity in West
Africa
ii. To discover the measures that can be implemented to control urbanization in West
Africa.
iii. To know whether the current rate of urbanization can be a driver or mechanism of
economic development through increase in agricultural productivity in West Africa
1.4 Research Hypotheses
The following are tested in the study
Hypothesis One:
H0: Agricultural productivity in West Africa does not depend on urbanization.
Hypothesis Two:
H0: There is no positive relationship between urbanization and agricultural productivity
Hypothesis Three:

19. 9
H0: Urbanization in West Africa is not distorted compared to agricultural productivity in West
Africa
1.5 Scope of the study
The study covers the periods between 1989 and 2010. The study examined data on population
density, agricultural productivity in terms of labour productivity and specific relevant
information which will include the challenges of urbanization in West Africa. The scope of this
study is limited to 14 out of 16 countries in West Africa.
1.6 Justification of the study
This research will be significant in numerous ways. It will be of immense benefit to the
government and policy makers for the following reasons. As a result of rapid urbanization from
rural to urban areas experienced in West Africa it is now a need to ascertain how the current
available resources will provide for the needs of the contemporary generation without
compromising the needs of the upcoming generation. Due to this, it is of great importance that
people must know how urbanization can play a crucial role on agricultural productivity thereby
affecting the economy positively.
1.7 Structure of the study
This research study is divided into five chapters, each deals with different aspects of the study.
Chapter One takes care of the introductory aspect of this study which includes the background
of the study, statement of problem, objectives of the study, justification, research hypothesis,
methodology, data sources and limitations of the study and the structure of the study.

20. 10
Chapter Two is concerned with the review of past literatures by previous researchers and most
importantly their findings. Chapter Three is about the theoretical framework, the research
methodology and model specification of the study. Chapter Four is about the analysis of the
study and also presents the results of our estimated models. Finally chapter Five is the
summary of the major findings emerging in this study and it also includes my
recommendations and concluding remarks.

21. 11
CHAPTER TWO
LITERATURE REVIEW
2.1 Introduction
Urbanization is necessary for achieving high growth and high incomes. The initial stage of
urbanization is very beneficial and can also be painful at the same time. Therefore managing
urbanization will affect the various aspects of a country like politics, social norms, institutional
change and the financial system in place (Annez and Buckley, 2009). During the past three
decades, the cities of the developing world and most especially Africa have witnessed a
remarkable and in many ways unprecedented demographic spurt. Regardless of the slowdown
in rates of increase in the past few years due to decreasing wages thereby shrinking social
services, and changing demographic trends, modern-day urban areas remain the growth poles
of economic progress and the lightning rods of political and social unrest. This predicament is
not as evident in any other place apart from the crowded cities of sub-Saharan Africa, where
projections of urban population growth remain the highest in the world (Todaro, 1997).
Fay and Opal (2000) stated that sustainable economic growth is always accompanied by
urbanization. In most African economies we see the inverse of this. Just because urbanization
occurs without growth in some African economies and it is evident that urbanization in Africa
is distorted. It can be also be said that urbanization in sub-Saharan countries is not always
accompanied by sustained growth. Also in the economic downturns, the poor and the migrants
don`t often flock back to rural areas. It will be burdensome for any country to attain middle-
income status without a significant drift of the population into cities. Through this assertion, it
is possible to say urbanization and growth works hand-in-hand. In other words one will lead to

22. 12
another. Urbanization occupies a puzzling position In the case of development and growth
theory (Annez and Buckley, 2009).
Urbanization is a gradual process and it makes it impossible for new cities to pop up out of
nowhere. Countries start from low human capital levels where all economic activity is in
agriculture and at some critical value of human capital accumulation, urbanization starts
(Henderson and Wang, 2004). Apart from urbanization being a gradual process it can take on
different patterns in different settings. This is so because many countries conform to standard
views of some structural transformation. In such an economy, Urbanization ends up being a
bye product of either pull from industrial productivity growth or a push from agricultural
productivity growth. In such countries urbanization occurs with industrialization and thereby
generates production cities (Gollin, Jedwab and Vollrath, 2013).
The twin pressures of rapid urbanization and a fast growing population have wreaked havoc on
agricultural land relations and land management in Temale (Ghana). Agriculture which is the
main source of livelihood of peri-urban dwellers is as a result of rapid urbanization because of
its problem of scarcity of land for agricultural purposes that will arise (Naab et al., 2013).
This chapter will focus on the review of literatures related to urbanization and agricultural
productivity in West Africa and sub-Saharan Africa in total and also to shed more light on
urbanization

23. 13
2.2 Review of Definitional Issues
All countries set boundaries between rural and urban population, the aspect of definitional
issues of urban areas varies among countries and from time to time it even varies within the
confines of a country. Naab et al. (2013) presented urbanization as being measured by
demographers as the urban population divided by total population of that region. Urbanization
is also defined as the annual rate of change of the percentage of people living in urban areas, or
the difference between the growth rate of urban population and that of total population. Urban
communities can be defined in many ways via population density, population size,
administrative boundaries or even the economic function of the country. Henderson and Wang
(2004) defined urbanization as the increase in the percentage of the national population that is
urbanized. The idea in urbanization is that large number of people quit farms so as to live and
work in the city. Only when there is an increase in the percentage urban dwellers than we can
say there is urbanization.
Urbanization is the process whereby large numbers of people congregate and settle in an area,
thereby eventually developing social institutions such as businesses and government to support
themselves. Urban areas which are now formed are characterized as relatively dense
settlements of people. The process of urbanization is a focal point for many sociological
concerns (Anthony, 2011). Urbanization moves populations from traditional rural
environments with informal political and economic institutions to the relative anonymity and
more formal institutions of urban settings, which is as result of the shift of the population from
rural to urban environments regarded as a transitory process. Urbanization within itself requires
institutional development within any given country. Urbanization separates families, most

24. 14
especially spanning through many generations as the young migrate to cities thereby leaving
the old behind in rural areas (Henderson, 2003).
Ramanchandra and Aithal (2013) stated that urbanization is the growth which is attained
physically in urban areas due to rural migration and even as the effect of towns or suburban
concentration transforming into cities. Some factors triggers urbanization through government
efforts which later result into improved opportunities for jobs, housing, transportation and
education. Likewise there is another term that has been confused which is urbanization rate, it
is defined as the increase in the percentage of the national population that is considered to be
urbanized, it is most rapid at low income levels and then tails off as countries become fully
urbanized (Henderson and Wang, 2004).
Fulginti, Perrin and Bingxin (2004) stated that productivity can be expressed as the output per
unit of input. Growth of productivity aims at not just capturing output growth but also
capturing output growth not accounted for by growth in inputs. Land, Livestock, machinery,
fertilizer and labour are considered to be traditional inputs. Agricultural land can be measured
as the sum of arable land and fixed crops available in thousand hectares. Agricultural labour
can be measured be looking at the number of persons who are economically active and
participates in agriculture preferably measured in thousands. Ukeje (2000) opined that
productivity in agriculture is the measure of how efficiently effective resources are used as
inputs for the production of goods and services required by the general public on the long run.
Productivity is an essential issue that is attached to agricultural development because of its
impact on the economy. Ukeje said for mankind to walk out of poverty and hardship the level
of productivity must increase.

25. 15
It can said that at the production level, agricultural productivity can be defined as the value of
output for a given level of inputs (Forum for Agricultural Research in Africa, 2006). The value
of output must increase faster and more than the value of inputs so as to increase productivity
in agriculture. Gains in productivity will come through some changes in the production process
as a result of more output per unit of input like land yields or labour or even from some
changes in production and market costs and therefore increases the profitability of farmers.
Urbanization is an irrevocable process which involves changes in vast expanse of land cover
and local ecology with the progressive concentration of Human population. Urban Sprawl
refers to excessive unusual growth near the periphery of the city boundary or in places where
there is the absence of planning and basic amenities are not available. Urban sprawl can also be
referred to as unplanned growth because it involves unsystematic and unappealing expansion
of an urban area into neighboring boundaries (Ramanchandra and Aithal, 2013).
Urbanization occurs as a result of large number of people deciding to concentrate in a
relatively small area so as to form cities. The world urbanization prospects report only presents
urban data that reflects on national definitions, which are challenged with the problem of
consistency (United Nations, 2012). It is important to note that places considered as urban in
one country may be seen as rural in another country. Good examples are countries like Angola,
Ethiopia and Argentina agrees that localities with 10,000 inhabitants or more is said to be
urban. Then any community with below 10,000 inhabitants is said to be rural. Hitherto other
countries in order to ascertain whether a community is urban or not, it is done through urban
boundaries centered on a mixture of population density or size and other economic and social
indicators.

26. 16
Urbanization is one of the striking global changes because it is a social phenomenon and also
the physical transformation of landscapes. Most especially in metropolises and places regarded
as mega-urban. This term urbanization anticipates trends with global and regional
consequences which are very difficult to forecast. Urbanization has expansion, compression
and also differentiation as the drivers.
Expansion in urbanization is said to be the spread of mega-urban regions and their intrusion
upon hinterland. Mega-urban areas are mainly dependent on catchments and supply areas for
essential resources, energy, goods and proper information flow so as to maintain and preserve
their metabolism. Large agglomeration characterized with the compaction of people,
knowledge, proper social interaction and also proper decision making process is regarded as
compression. Differentiation demarcates the possibility of increase and also the degree of
change in the society therefore it is regarded as one of the consequences because people will
have the opportunity to compare and also distinguish themselves and also welcome new
lifestyles.
2.3 Review of Theoretical Issues
Regarding existing literatures on the relationship between urbanization and agricultural
productivity there is a problem of inconsistency in variation because the term urbanization has
different definitions in all parts of the world. Also there is no unswerving measure of
urbanization. No country has grown to middle income without industrializing and urbanizing.
None has grown to the level of high income without pulsating cities that commands resources.
The rush to cities in most developing countries seems chaotic, but it is very necessary (Turok
and Mcgranahan, 2013). Also the city is one of the highest pinnacles of human creation,

27. 17
through agglomeration cities have the power to generate wealth and also enhance the quality of
life and also accommodate more people with smaller footprint at lower per capita resource
usage and emissions than any other settlement pattern.
China can be used to explain how urbanization can fuel industrialization, increase the level of
productivity, and also transform living standards of people. In 2011, China passed the historic
landmark of 50 percent of its population living in cities from only 20 percent in 1980. This
extraordinary speed of urbanization has reflected the strength of jobs growth in cities. Also the
average household incomes tripled. There is expected urban increment which will occur
globally of 1.8 billion people during 2025-2050, this will have India become a major
contributor with 377 million people, then will be followed by China with 205 million people.
Both countries are regarded as the top two most populous countries in the world and it is
expected that both countries will account for 32 percent of urban growth spanning from 2025-
2050. It has been projected that by 2050, China will have the largest urban population of 1
billion people and India will have 0.9 billion people (United Nations, 2007).
2.3.1 The Theory of Agglomeration Economics
Turok and McGranahan (2013) presented some clarifications that must be made about some
concepts under this theory and also about the benefits that can be derived from economic
concentration. The first concept is the concept of division of labour. This explains the gains
derived from productivity which later develops to growth from the act of specialization. Here
firms divert their attention to special tasks or even products that will later give way to
enhanced skills and most importantly greater efficiency. At city level it is possible to apply
specialization, this can be done because the point when external trade starts growing and the

28. 18
level of competition becomes deepen at this point specialization becomes very essential.
Through specialization other benefits can be derived from bringing a group of functions to the
center of attention through which places become heir to some distinct merits.
The second concept is that of economies of scale. This can be sub-divided into two namely;
internal economies of scale and external economies of scale. Starting with internal economies
of scale, it is not really applicable to agglomeration economics because they are internal to the
firm and commands lower unit costs via large-scale production. Our focus will be on external
economies of scale. It is otherwise known as agglomeration economies. They are the benefits
derived from the act of being attached to other firms so as to reduce costs attributed to
transactions like communication and transportation, as well through shared information derive
some gains attached to network effects. This is so because it has been observed that the bigger
the network, the wider the base of knowledge and also the intelligence that will later be useful
to learn from (Duranton, Gilles and Puga, 2004).
Agglomeration economies is broad and the contents are nearness to a bulky labour pool,
customers, suppliers and most importantly competitors within the same industry regarded as
localization economies, and also firms that exist in other industries regarded as urbanization
economies. External economies of scale comprises of three extensive functions, the functions
of learning, sharing, and matching. Looking at this serially, the function of matching comes
first because cities help firms to match their unique requirements of firms for some essential
contributions like Labour, material inputs and also premises better than towns (Duranton et al.,
2004). Through agglomerations firms will not be having problems in mixing and matching
their resources with ease. The next function is concerned with sharing.

29. 19
As a result of scale of activity, cities make available to firms a wider range of services which
are shared and also infrastructure. Cities bring about a nexus between customers and suppliers
via transportation that unites more destinations and also more logistics to take care of exports
and imports. The third function is that of learning. Firms enjoy better-quality in the flow of
information in cities. This function creates a self-reinforcing virtuous circle that encourages
creativity and generates growth from within. Summing all these functions together, it is
observable that the merits of external economies of scale are significant just because they are
collective and not static (Hall, 1998). Urbanization will necessarily make economic output to
increase not just because of the existence of agglomeration economies. This is so because of
the gains from concentration via overcrowding, increasing congestion amongst others.
It is very possible that the point of equilibrium between agglomeration diseconomies and
economies to have impactful influence on the economy. This can either make economies
stagnate, grow or even reach the point of declining in cities. Advantages derived from
agglomeration may vary in and out of the sectors in the economy owing to the existing
relationship between urbanization and growth. Land and housing markets function effortlessly
and local authorities are known to be alert to market failure so as to ensure that people and also
firm can now with ease relocate thereby making suitable land, road and rail network could also
be made available to accommodate the people. In conclusion of this theory, Urbanization
implies a decrease in the portion of rural dwellers and importantly not just more urban
dwellers. In a scenario where overpopulation in the rural area is becoming a problem,
urbanization can be used to help out. It is crucial to know that all forms of urbanization will
have the same level of shock on productivity in rural areas and also incomes (Dorosh, Paul and
Thurlow, 2012)

30. 20
2.3.2 The Lewis two sector model
This theory is attributed to W. Arthur Lewis. He came up with this theory so as to elucidate the
workings of an underdeveloped economy via the migration from rural sector to the urban
sector (Todaro and Smith, 2011) This theory is simply about transformation. It captures
transformation of a traditional economy based in agriculture into a current industrialized
economy. This theory presupposes a rural sector that is generally ascribed by surplus labour
which is possible to be swallowed up by the modern sector. It will be swallowed up without
any form of disruption on the side of the production output on the country-side (Todaro and
Smith, 2011). So far as surplus labour exists, the modern sector will be charged with the
responsibility of providing minimum wages even though at a level of higher value than the
profits enjoyed via agricultural labour. This is the reason behind the attractiveness of urban
labour (Nordhag, 2012).
The assumption behind this theory is that since the modern sector will enjoy some profits, this
marginal profit will be channeled into modern sector so as to increase and also improve the
production level which will later cause a demand of more employees (Mishra, 1969). As
surplus labour is increasingly swallowed, the urban labour force becomes very scarce. This will
later result in higher wages since it is a necessary condition in order to employ agricultural
workers that do not fall in the bracket of surplus labour. It is important to know that in this
model, everybody in the traditional workforce will be employed by the modern sector. This
will later cause labour demands to stop increasing because of the presence of capital-intensive
actions.

31. 21
This theory has been criticized because it cannot be applied in today`s less developed countries
in West Africa. The model of Lewis is just a reflection of the process of industrialization of
more developed countries. The assumption that in order to increase production, accumulated
capital is reinvested Todaro and Smith (2011) opined that the process of investment may not
happen at all at the beginning. The study stated that there is no form of assurance that owners
of companies will decide to invest. This is so because firstly, Humans cannot be predicted and
they can make different choices about what to do with profits. Then due to the problem that job
seekers will suffer instead of enjoying because the process of reinvesting can be in different
forms like purchasing machinery to replace labourers which is a good form of labour saving
action.
Although the Lewis two sector model is widely known but it is challenged with the problem
that not all the people under the rural workforce is willing or ready to accept jobs in the
modern sector (Todaro and Smith, 2011).
2.3.3 Todaro`s Rural-Urban Migration Theory
Rural to urban migration remains a significant part of urbanization in developing countries of
which West Africa is a member. This makes this theory suitable for the study of urbanization
in West Africa which has been subjected to heavy urbanization over the years. This theory was
developed because of the labour migration in eastern and southern Africa due to colonial rule.
Todaro (1969) laid emphasis on pull and push factors in migration and He explained that rural-
urban migration was a response to the predictable income rather than the current income
differentials that exists between rural and urban areas. This model was based on four
assumptions

32. 22
i. Migration is propelled principally by rational economic considerations, relative costs
and benefits of both a financial and psychological nature,
ii. Man`s decision to migrate solely depends on expected rather the current urban-rural
wage differentials,
iii. He also said the probability of obtaining an urban job is inversely related to the urban
unemployment rate
iv. Since urban In-migrants expect positive urban-rural expected income differentials, the
phenomenon of persistent high rate of urban unemployment represents a logical
consequence of the imbalance in economic opportunities between urban and rural
areas.
2.3.4 The Harris-Todaro model on Migration
This theory was published in 1970. Todaro and Smith (2009) said this model is the equilibrium
form of the Todaro migration model. The intention of this model is to explain the dynamics of
the process of people moving from rural to urban areas. Conventional economic theories on
rural to urban migration are misleading and also not satisfactory (Harris and Todaro, 1970).
The authors of this theory opined that previous theories assumed that migrants have full access
to waged employment and it is the only driving force behind migration. Harris and Todaro
stated that other theories did not look at the situation in which many rural-urban migrants end
up not being employed and that reality is completely different.
This theory has a unique setting in which there is a rural area where only agricultural products
are produced via the totality of the labour force or by removing restrictions restricting labour
force from migrating so as to seek waged labour (Harris and Todaro, 1970). Goods are

33. 23
manufactured in the urban areas by waged employees. This theory argues that rural-urban
migration will not stop unless profits from working in the agricultural sector exceed the urban
minimum wage. This theory was able to comprehend the reason behind high unemployment
rates experienced in urban areas. The study then attributed it to urban minimum wages which
are mostly fixed synthetically by some institutions in such a way that it is not compatible with
the free markets which is very evident in developing countries. This will later result in a state
of equilibrium where the possibility of gaining higher incomes via rural-urban migration is
matched with the risk of unemployment.
Harris and Todaro (1970) also affirmed that before the occurrence of any form of rural-urban
migration the individual involved carefully calculates the income expected and coupled with
the chance of getting employed at all. Both factors are then balanced against each other. They
also made it clear that rural to urban migration is likely to occur if the wages paid in urban
areas are much higher that what is paid in rural areas regardless of the risk of unemployment.
The study came to a conclusion that the chance of getting a well-paid job will prevail over the
risk of the individual not getting a job. Due to all this high unemployment rates and rural to
urban migration will not cease in less developed countries (Todaro and Smith, 2009).
Since this theory was based on future equilibrium, Charles H. Woods criticized the theory and
was of the opinion that equilibrium based theories fail to address some very essential factors. A
good example of the factors mentioned in the study is Ethics. Woods further stated that in view
of the fact that this theory assumes that rural to urban migration will later regulate itself. He
then concluded that this will discourage state actions channeled to get in the way of migration.
Woods was of the opinion that since the state lacked control it will be possible for job seekers

34. 24
to be exploited. The study also criticized the assumption that people are propelled to migrate
because of potential income gains. This assumption is not in any way realistic because they are
other fundamental reasons beneath rural-urban migration. Woods (1982) said an individual`s
decision to migrate does not depend only on the rational choice but it is as a result of many
socio-economic factors.
2.3.5 Mabogunje`s Central Place Theory
The theory was concerned about welfare and made mention that it remains implicit to the
analysis of the study which is attributed to Mabogunje This theory established the link that
exists between central cities, the types of goods and services found in them, the spacing
between cities and most importantly the travel-willingness or travel-frequency of individuals
(Filani, 2006). The study presented central places as small towns that offer lower order goods,
central places will now constitute a hierarchical system where higher order places will be at the
top and lower order central places will be at the bottom. The study further explained that there
are some factors that can cause threshold population to decrease drastically.
The study also referred to central place as a settlement which provides some specific services
for the population that resides around it (Filani, 2006). Under this theory Mabogunje
mentioned some simple basic services which the study later grouped to Low and high order.
The study presented settlements with low order services are classified to be low order
settlements then those with high order services are classified to be higher order settlements.
Also a distinct line was drawn between threshold population and sphere of influence. Sphere of
influence is that area that is subjective to the central place while the study also presented
threshold population the minimum population size needed to adequately maintain a service.

35. 25
Some fundamental assumptions of this theory are as follows: the population is assumed to be
evenly distributed the existence of similar purchasing power and resources are evenly
distributed and the existence of isotropic surface.
2.3.6 Ravenstien`s Laws of Migration
This theory comes under the neo-classical equilibrium perspective and it is attributed to Ernst
Georg Ravenstein. This theory perceived migration from another perspective and it stated that
it remains an inseparable part of a Nation`s development. Ravenstein was of the opinion that
migration was solely caused by some economic factors. Migration patterns of this were
assumed to be manipulated by population density and the distance (Ravenstein, 1885). The
theory expects people to move from low income areas to high income areas due to rationality.
Also people are expected to move from densely populated areas to an area that is lightly
populated in search of comfort. This theory remained strong after it was criticized by many
scholars. These laws are now seen as empirical generalizations based on Ravenstein`s
calculations from the census they had in Britain. The following generalizations formed His
laws.
i. Migrants move mainly over short distances. There is an exception for people going
longer distances because of great centers of industry and commerce.
ii. Most migration is from agricultural to industrial areas.
iii. Large towns grow more by migration than through natural increase.
iv. Migration increases along with the development of industry, commerce and transport
v. Each migration stream produces a counter-stream.
vi. The major causes of migration are economic

36. 26
vii. Females are more migratory than males.
2.4 Review of Methodological and Empirical Issues
According to a survey by United Nations (2013), most policy makers resist urbanization rather
than welcoming it. The organization was of the opinion that economies rarely grow without
their cities growing. Policy makers would prefer to stem the urban tide and see people return to
rural areas. They brought to the knowledge of the people that one of the major causes of social
and political headaches, such as over-crowding, concentrated squalor, crime, street violence
and quick transmission of disease is urbanization at the rapid stage. This is evident in West
Africa. United Nations agreed that out of all the regions in the world, West Africa remains one
of the least urbanized.
Todaro and Smith (2011) said regardless of the real progress experienced, close to 2 billion
people in the gradually developing world will expect a scanty society which is sufficient for
their agricultural needs. The study agreed that over 3.1 billion people resides in rural centers in
developing countries as at 2010, in which they said a quarter of the people are living in
extreme poverty. Todaro and Smith also agreed that sub Saharan African countries suffer the
most because they have over 65 percent of people living in rural areas. They also discovered
that two-thirds of the world`s poorest people are based and situated in rural centers and most of
them engage solely in subsistence agriculture. This is the reason why almost all the people
living in rural centers being survival minded. United Nations (2009) estimated that for the very
first time, more than 1 billion people did not have enough agricultural products to meet their
fundamental dietary needs.

37. 27
The behaviour of farmers in developing countries most times looked absurd to many observers
who are not aware of the farmer`s great effort which is like a routine just to subsist. It was
recently that observers were able to comprehend the wobbly nature of subsistence living and
the fact that farmers were avoiding the risk of the unknown. Agriculture was said to play two
roles in economic development namely supportive and passive roles. They emphasized that the
principal purpose of agriculture is channeled at providing low priced food which is adequate
and also the manpower required for the expansion of the industrial sector which is the leading
sector and also the heart of the economy.
The contributions of agriculture to economic development were introduced by Simon Kuznets.
The study postulated that agriculture made four contributions, first is the product contribution
of inputs for industries like textiles and food processing, second contribution is that of foreign
exchange contribution that ensures revenues generated from exporting agricultural products are
used to import capital equipments for the country. Third contribution according to Kuznets is
the area of market contribution of increasing rural incomes thereby simulating more demand
for consumer products. The final contribution is that of the contributions made on the factor
market. In the present day most development economist share the opinion that apart from
playing a passive, supportive role in the process of economic development, the agricultural
sector in particular and the rural financial system universally must play an indispensible part in
any overall strategy of economic progress most especially for those countries classified as low-
income developing countries (Todaro and Smith, 2011).
Gollin et al. (2013) made it clear that there are many theories that link urbanization and
industrialization together but the relationship between both of them is absent in developing

38. 28
countries most especially West Africa. The study was able to make this statement because
many countries endowed with rich resources have urbanized without increasing output in
anyway. They carried out their study through the construction of a model of structural change
which accommodates two pathways to urbanization. The first pathway was tagged production
cities, it is about the distinctive movement of the factor, labour from agriculture into industry.
The second pathway, consumption cities which are driven specifically by income effect of
some endowments thereby rents are spent on goods and services in urban areas. They stated
that urbanization is not in any form a homogenous event.
Gollin et al. (2013) applied the use of cross-sectional regressions with a sample of 116
countries and made urbanization for 2010 the dependent variable, there regression was
population weighted and they regressed on the share of natural resources in GDP from 1960-
2010 on the average, they also added the share of manufacturing and services in 2010. Through
their cross-sectional and panel robust checks they discovered that urbanization has a positive
relationship with both share of natural resource in GDP and share of manufacturing and
services. Most alternative theories of urbanization made their results spurious because it was
evident that some parts of the world experienced urbanization without any form of economic
development. They said this was due to pull and push factors. So as to make the model
complete, Other important controls were introduced.
The study discovered that people who export natural resources were able to calculate
urbanization rates in many ways. Regardless of the dummy variable added to the model and the
inclusion of some controls, the positive relationship that exists between natural resource
exports and urbanization rate was not distorted. Also the study discovered that the relationship

39. 29
between them was very strong. Also their study experienced some standard deviations;
concerning the portion of natural resource exports in GDP had a 0.48 standard deviation in the
urbanization rate and manufacturing and services in GDP had a 0.39 standard deviation in the
urbanization rate. Furthermore, some tests were carried out so as to ascertain whether the result
was robust. This was done through the use of multivariate panel analysis with a sample of 112
countries and a period of 6 years with 10 year intervals.
In controlling industrial booms, share of manufacturing exports was added to GDP because for
2010 the share of manufacturing and services was not available. The standard error they got at
country level were clustered, this led to the discovery of unconditional results. The study made
some additions to the model so as to robust it notwithstanding the correlation between exported
natural resources and urbanization remained strong. The result of the multivariate panel
analysis was seen to be five times lower than the result of the cross-sectional analysis.
According to the study both methods cannot be really compared but they made it clear that
panel regression remained special because it considers the short run and as such it only
measures the short run effects of short-term variations and it permitted the inclusion of country
fixed effects so as to control time-invariant heterogeneity (Gollin et al., 2013).
The panel regression supported the hypothesis that exported natural resources could be
endogenous to the urbanization process. The study also established that the variable
urbanization has no impact on natural resources exported in the next period also even the
reverse has no effect either. Another observation from the study was that there were no
impactful effects from cash crops unlike what was discovered for petroleum products and
mining products. Oil had stronger effect on urbanization than any other mineral resources. In

40. 30
conclusion the study contradicted urbanization and industrialization being used
interchangeably or seen as identical because the study made stated clearly that resources
exports are considerably linked to urbanization rates Gollin et al. (2013).
Gollin et al. (2013) affirmed that countries endowed with natural resources will definitely
experience urbanization without any form of industrialization. Same countries that urbanized
without industrializing achieved it by importing most of their food and goods that are tradable
and most importantly resources endowments will create consumption cities thereby increasing
income that is surplus then later shift workers away from the sector that is tradable. This study
also presented the components of urban employment which was considered to be twisted with
personal services rendered and local retail. Countries with deficient resource endowments will
urbanize in production cities which are mainly driven by the substitution of labour that is
aimed at the tradable sectors like finance.
Mabogunje (2002) made use of factor analysis to help Him identify some important
dimensions of the process of urbanization in Nigeria. This study was able to do so by using 32
variables and conclusion that seven factors accounted for the 84.3 percent of the aggregate
variance of the original data (Filani, 2006). This study revealed some fascinating secrets about
Nigerian cities and declared some characteristics of urbanization that are heavily implanted in
masses of data. Mabogunje made use of some theories of urban structure which includes the
multiple nuclei theory, the sector theory and the concentric zone theory. The study applied
three theories. First theory was the concentric zone theory, then the sector theory and the
multiple nuclei theory. The last theory remains very crucial in the understanding the nature of
Nigerian cities.

41. 31
The study made use two cities in Nigeria namely Ibadan and Lagos. Ibadan according to the
study has traditional and modern characteristics. The study started with that of the preservation
of the contrasting both nonresidential and residential neighborhoods that was present in the city
of Ibadan. Ibadan was characterized by high density, poor environmental quality amongst other
factors which will not stop expanding into new metropolis. The study stated some factors
responsible for the resistant to change which was found in traditional people after enjoying
policitcal power. This study introduced the concept of central business districts. Mabogunje
(2002) stated that twin central business districts will be very compatible in the city of Ibadan.
After the study affirmed that most cities represent an amalgam of two different urban
processes. Some problems were identified like the problem of its slum areas and also the
problem of easy circulation. Mabogunje was of the opinion that Lagos was not a traditional
city unlike Ibadan.
Nordhag (2012) discovered that sub-Saharan Africa is in a way diverse regarding the modern
extent of urban population. In 2009 the range of urban population was around 74.82 percent,
then 16.12 standard deviation, 37.95 mean value and median 37.52. There is no uniformity in
the level of urban population in sub-Saharan Africa. That remains the reason why people were
permitted to talk about the entire region`s level of urbanization Although there was an epitome
of truth in generalizing the region because the trends were similar. Nordhag believes that both
urban population growth and Urbanization will increase rapidly in sub-Saharan Africa more
than the way it has increased in the past two decades. Also countries that started urbanizing a
long time ago are supposed to have developed well especially in the area of infrastructure and
also in some facilities that will enable more urbanization growth.

42. 32
Nordhag (2012) performed two correlation analyses so as to ascertain why some countries in
sub-Saharan Africa have discrepancies in the extent of their population considered to be urban.
The first correlation was looking at the urban population of earlier years and that of year 2009.
It was discovered that for 1999 and 2009 the level of correlation was very intense but
subsequently correlation stopped. This result shows that existing urban population is a function
of urban population growth. The second correlation analysis, the independent variable was the
value of urban population dating 10 years back and the dependent variable was urban
population of a given year. The result showed that correlation between the two variables was
very strong and intense. This was so because it was discovered because of strong correlation
that existed between 1960 and 1969. From the results it is clear that in sub-Saharan Africa
urban population is escalating for those countries already have a good number of urbanization
already.
The study of Nordhag shows that the process of urban population growth and urbanization
must be viewed from more than one perspective so as to get desired results. Also it shows that
explaining the workings of urbanization with theories is not as hard as evaluating the impacts
of urbanization and the aftermaths. The study could not prove whether urbanization has a
positive impact on the living standard of the people. Instead it presented a clear view that
urbanization is a twisted process because it depends on a number of factors and conditions. The
primary driver of urban population growth in sub-Saharan Africa remains high nativity.
Although both Lewis two sector model and the Harris-Todaro model on migration believes that
urbanization depends on rural urban migration.

43. 33
Matsuyama (1992) made it clear that between agricultural productivity and industrialization
there is a positive link. This is so because rising productivity will in a way increase food
production and will make it possible to feed the growing population based in the industrial
sector. If more food items can be produced with less labour, the surplus will be transferred to
the manufacturing sector thereby affecting industrialization positively. Also if high incomes
are generated in agriculture there will be an increase in demand for most industrially produced
items. A model of endogenous growth was constructed to demonstrate the relationships that
exist between agricultural productivity and growth performance. This was done with standing
foundation of two assumptions which made it clear that agricultural productivity can only be
determined exogenously and that economic openness is the main determinant of relationship
between urbanization and agricultural productivity.
Li, Florax and Waldorf (2013) introduced spatial regression models that made provisions for
smooth coefficients. The study discovered that higher productivity in the agricultural sector
with less man power will allow the migration of labour into the industrial sector. It was
discovered that low urbanization that was experienced in the old can be attached to low
agricultural productivity. It was clearly explained why agricultural productivity improvements
remain a necessary force that will help push labour into urban activities. The study discovered
that in order to discourage rural-urban migration, agricultural productivity must increase
thereby making rural wages to increase.
More than 60 percent of the populations in Ghana are involved in agriculture. This made
agriculture a major source of employment of the people. The unemployment rate went up
because the agricultural sector was deprived of land. This happened because major agricultural

44. 34
lands were converted to residential buildings or structures. This led to low agricultural
productivity which reduced the standard of living of the people and made food insecure
because people were not certain of being fed (Naab et al., 2013).
2.5 Conclusion
It is now possible to say urbanization and industrialization cannot be used in place of each
other neither are they synonymous. This could only be said after the review of past works. The
sustained increase of the urban population combined with the pronounced deceleration of rural
population growth will result in continued urbanization. This will increase the proportions of
the population living in urban areas. Understanding the dynamics of urbanization can help
policy makers moderate its costs rather than worsen them. Also low urbanization brings about
low agricultural productivity.

45. 35
CHAPTER THREE
THEORETICALFRAMEWORKAND RESEARCHMETHODOLOGY
3.1 Introduction
In this section of the study, an attempt is made so as to carry out through a model, a conclusive
study to establish the relationship between the variables in the system. Urbanization involves a
process of growth. As said in the previous chapter, people migrate to urban areas so as to enjoy
better life but they fail to return to the rural areas when they discover that the dream of the
better life they projected is in fact not attainable because of the high rate of competition for
jobs in urban centers and other essential needs. This chapter also presents the specification of
model, estimation techniques, apriori expectations and also the criteria for making decisions
3.2 Theoretical Framework
Henderson (2005) models the urbanization process and how urbanization in a country is
accommodated by increases in numbers versus population sizes of cities in an endogenous
growth context where political institutions play a key role. The paper estimates the equations of
the model describing growth in city numbers in a country and growth in individual city sizes,
using a worldwide data set on all metro areas over 100,000 from 1960-2000.
Institutions and the degree of democratization and fiscal decentralization, as well as
technological advances, strongly affect growth in both city numbers and individual city sizes,
with the effects on individual city sizes being heterogeneous. Technology improvements help
bigger cities, with their complex infrastructure needs, relative to smaller ones; but increasing

46. 36
democratization levels the playing field across the urban hierarchy, allowing smaller cities
greater ability to compete for firms and residents. These two opposing effects on the relative
sizes of bigger versus smaller cities appear to have left the overall relative size distribution of
cities worldwide unchanged over the time period.
Eaton and Eckstein (1997) normalized city sizes by the average size of cities in the relevant
sample in the time period. Second, they altered the relevant sample in each period, raising the
minimum size absolute cut- off point to keep the same relative size and standard to be a city. A
ratio of the minimum (100,000) is taken to the mean (495,101) size for 1960 and the ratio
(.2020) is applied to 2000 (Black and Henderson, 2003, Abraham, 2009). He therefore
assumed the cut- off point to be a city in the sample for a particular year to be the first s cities
ordered by size such that s+1 city would be below the relative size, or we choose s such that in
time t
Where N1 (t) is the population of city i in time t. For the year 2000, out of a possible 2,684
cities in the world over 100,000 this gives a number of 1,644 cities with an average size of
1,009,682 and a minimum absolute size city of 204,366.
This mirrors results in the literature which suggest urban concentration as measured by either
primacy (the ratio of the population of the largest city to national urban population) or a
Hirschman-Herfindahl index has an inverted-U relationship with per capita income (Wheaton
and Shisido, 1981 and Davis and Henderson, 2003). The idea is that at low levels of
development, initial urbanization is spatially concentrated because resources for urban

47. 37
infrastructure and inter-city transport infrastructure are limited; skilled urban workers are in
short supply and knowledge is limited and spatially concentrated perhaps at points of entry to
international markets. As the economy develops, it garners the ability to disperse and the
economy diversifies. But the effects are fairly modest. The OLS estimation method was used to
estimate his results for the relationship between urbanization and economic development.
3.3 Research Methodology
The econometrics approach will be used and the panel data analysis will be applied. This is
because the dataset of the study deals with the observation of entities across time. The panel is
the combination of both the cross-sectional and time series that is it has space as well as time
dimension. This econometrics method is chosen due to the nature of this study as it covers 14
countries in West Africa from 1989-2010.
Gujarati and Porter (2009) presented the following as the advantages of panel data method
according to Balgati.
i. Panel data through its combination of both time series and cross-sectional data gives
more informative, efficient data, chance for variability, makes provisions for degrees of
freedom and it is known for less co linearity among variables used.
ii. Panel data could also enable us to study more complicated behavioural models such as
economies of scale and technological change than by only using cross section or time
series data.

48. 38
iii. Panel data helps or allows the control of variables that cannot be measured or observed
such as cultural factors or variables that change over time but not across entities such as
national polices. Therefore it takes account of individual heterogeneity.
In summary, a panel data analysis improves the quality of our empirical analysis which may
not be feasible seeing either cross-section or time series data.
The following are the drawbacks of panel data method:
i. The issue of data collection could arise.
ii. Since it consists of both cross-sectional and time series data, the issue of
heteroskedasticity and autocorrelation will be needed to be addressed.
According to Torres-Reyna (2013) panel data analysis could be specified using either the fixed
effects model or the random effect model as shown below.
The equation for the fixed effects model is given as:
Yit = β1Xit + αi + uit (1)
Where
αi (i=1….n) is the unknown intercept for each entity (n entity-specific intercepts).
Yit is the dependent variable where i = entity and t = time.
Xit represents one independent variable ,
β1 is the coefficient for that IV,

49. 39
uit is the error term
While the equation for the random effects model is given as:
Yit = βXit + α + uit + εi (2)
Where
εi= Within-entity error
uit= Between-entity error
α= is the intercept value with no (i) because it is assumed to be a random variable.
Therefore, this study will be using the panel data analysis in studying the role of urbanization
on agricultural productivity in West Africa.
3.4 Model Specification
The study examines the empirical relationship between urbanization and agricultural
productivity in West Africa.
Y=AKα Lβ
Since the study is concerned with productivity we have to introduce the Cobb-Douglas
production function for simplicity purpose.
The model for this study can be specified below in an implicit or functional form:
AGPRO=f (A,URB, LFE,EDU, INDPRO,AGPOP)
Where

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AGPRO = agricultural productivity
A= level of total factor productivity
URB = urbanization level
LFE = life expectancy
EDU = education level in terms of primary school enrolment (gross percentage)
INDPRO = industrial productivity.
AGPOP = agricultural population.
Bloom, Canning and Sevilla (2004) specified there model in an aggregate production function.
This study will also follow use the same aggregate production function.
AGPRO =AURBαLFEβe ϕ1EDU+ ϕ2INDPRO+ ϕ3AGPOP (3)
We proceed by transforming the above equation into a log-linear form. After which we will be
left with the equation for the log of AGPRO at country i at time t.
LogAGPROit =ait+ αlogURBit+ βlogLFEit+ ϕ1logEDUit+ ϕ2logINDPROit+ ϕ3logAGPOPit
(3a)
We must note that equation 1 stated some human capital outputs (EDU and LFE) as powers of
exponential and also the benefit of this form which is functional is that Log AGPRO depends
on the levels of health and education which was captured with the proxies EDU and LFE.
Urbanization level ait in country i and time t is not observed and is therefore assumed to be an
error term in the process of estimating the equation.

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Since its a panel study, the model above can be stated in two forms either fixed model as seen
previously in (1) or the random effects as seen in (2)
For the fixed effect model, we can explicitly sate the above model as:
LogAGPROit =ai+ αlogURBit+ βlogLFEit+ ϕ1logEDUit+ ϕ2logINDPROit+ ϕ3logAGPOPit. + μit
(4)
Where i=1,2,….14 which represents the entities(countries), t=1,2……20 which is the time
period for the variables, ai is the unobserved or heterogeneity intercept and μit is the error term
with a mean of zero(0) and also constant variance. Above all we must note that the error term
is normally distributed.
For a random effect model, we will state the model as :
LogAGPROit =ai+ αlogURBit+ βlogLFEit+ ϕ1logEDUit+ ϕ2logINDPROit+ ϕ3logAGPOPit + wit
(5)
The major difference is that wit = εi + μit
Furthermore the fused error term wit comprises of two components the first which is known as
the within-entity (εi) also known as individual specific error term. The second is the between
entity (μit) also known as the combined time series and cross-section error component.
3.5 Technique of Estimation
Panel data analysis was used to examine the role of urbanization on agricultural productivity in
West Africa and this as said before is because of the nature of the data which consists of
different entities (countries) at different time periods. Two methods of estimation are involved

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under the panel data analyses which are the fixed effects and the random effects. The former
(fixed effects) assumes that there is need to control the unique characteristics of the entities and
its impact or bias on the predictor variables. Therefore it reduces the effect that the time
invariant characteristics may have on the predictor variables so that the net effect of the
predictors can be seen. On the other hand, random effects assume that the variations across
entities are random and do not correlate with the predictor variables in the model. This means
that the time invariant variables are included in the model unlike in the fixed model where it is
absorbed by the intercept.
To determine which model is suitable and efficient for the model which may either be the fixed
or random effect, the Hausman’s test will be run and this will test whether the unique errors
(ui) are correlated with the regressors or not. Under the Hausman’s test, the null hypothesis is
that the model is random effects while the alternative is that the preferred model is fixed
effects.
Other tests include the test for random effects and cross-sectional
dependence/contemporaneous correlation using the Breusch-pagan LM test, test for
heteroskedasticity, test for serial correlation using the lagram-multiplier test and tests for unit
roots and stationarity.
3.6 Justification of Variables Used
AGPRO: Agriculture value added percentage of workers is used to measure agricultural
productivity. It measures net output of a sector summing up all outputs then removing
intermediate inputs. It is perfect because it is done calculated without making provisions for

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deductions of depreciation of assets and depletion and degradation of natural resources. Most
importantly it is in constant of 2005 United states dollars.
URB: Urbanization level is derived by dividing the urban population by total population. It is
measured as the urban population expressed as a share of the total population. This shows the
level of urbanization in a country. Li et al. (2013) made use of this variable in their study.
LFE: Life expectancy at birth: This depicts the number of years a newborn baby would live
given that the patterns of mortality at the point of birth remains same throughout the infant`s
life. This an addition to knowledge
EDU: education level (primary school enrolment) School enrollment, Primary (percentage
gross) is a proxy for education is used in this study because the rate of enrollment into primary
education is very important in determining productivity and also help determine the level of
educational attainment in a country and also at the primary level of education, one should
possess the required skill be able to read and write. This is very essential for any economy.
INDPRO: This variable is very important because it controls the urban pull side of
urbanization. It was adopted from the Lewis 2 sector model. It is measured by industry value
added per worker.
AGPOP: This variable measures the total population in agriculture
3.7 Apriori Expectation
The apriori expectation for the relationships between the explanatory variables and the
dependent variables of the model based on economic theory as explained below. It is expected
that a, α, β, ϕ1, > 0 while ϕ2 < 0.

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3.8 Data Employed, Measurement and Sources
The panel data covers the period from 1989 to 2010. The table below shows the variables,
measurement and sources.
Table 3.1 Variables, Measurements and Sources
Source: Computed by Author
VARIABLE MEASUREMENT SOURCE
AGPRO Agriculture value added per
worker (constant 2005 US$)
World bank`s World Development
Indicators (WDI) 2013 and Africa
Development Indicators (ADI) 2012
URB Urbanization level ADI 2012
LFE Life expectancy at birth ADI 2012
EDU education level (primary school
enrolment percentage gross)
ADI 2012
INDPRO Industry, value added (
percentage of GDP)
ADI 2012
AGPOP Agricultural population (FAO,
number)
ADI 2012

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CHAPTER FOUR
DATA ANALYSIS AND INTERPRETATION
4.1 Introduction
This chapter is concerned with the presentation of data, the analysis of data and also the
interpretation of data. The econometric and descriptive analysis of data is also carried out in
this chapter
4.2 Descriptive analysis
Table 4.1 shows the summary statistics for the variables used in this study, it contains the
mean, standard deviation from the mean, the minimum and maximum values of each
observation, the range, the skewness and also Kurtosis.
Table 4.1 SUMMARY STATISTICS OF VARIABLES
Variable Mean Standard
deviation
Variance Minimum Maximum Range Skewness Kurtosis
AGPRO 878.25555 773.9172 598947.9 140.2832 4654.71 4514.427 2.095079 7.773021
URB 0.3793506 0.0911537 0.008309 0.135188 0.61833 0.483142 -0.260333 3.471646
LFE 51.56698 7.073655 50.0366 37.18761 73.77405 36.58644 0.7699643 4.22663
EDU 78.55328 26.18808 685.8157 25.9866 139.6437 114.6571 0.0880591 2.275647
INDPRO 20.53479 8.62644 74.41546 1.882058 46.53131 44.64925 0.6548119 3.380506
AGPOP 6979760 1.01e+07 1.01e+14 84000 4.20e+07 41916000 2.704283 9.49042
Source: Computed by Author
The variable agricultural productivity (AGPRO) variable had a mean of 878.3, and a standard
deviation (SD) 773.9 from the mean. Urbanization level (URB) had a mean of 0.3794 and a

56. 46
standard deviation of 0.0912. Life expectancy (LFE) had a mean of 51.57 and SD of 7.07.
Education level which is primary school enrolment percentage gross (EDU) had a mean value
of 78.56 and SD of 26.19. Industrial productivity (INDPRO) had a mean of 20.54 and SD of
8.63. The variable agricultural population had a mean of 6979760 and SD of 0000000.1.
The maximum and minimum values are the highest and lowest values the function can
accommodate at any given point. Skewness is used in distribution analysis to measure
asymmetry of the distribution. It can be positive, negative or undefined. It is important to know
that it does not describe the relationship that exists between mean and median. Kurtosis is used
solely to measure the peakedness of flattening of the probability distribution of a real valued
random variable. It provides the shape of the probability distribution.
4.3 Empirical Analysis
Here some tests would be carried out so as to be able to estimate the results of the study
4.3.1 Test for multicollinearity
Multicollinearity is said to be a case in which there is the existence of linear dependency
among the independent variables used in the regression. In other words it means that there is an
existence of a relation between the independent variables. (LURB , LLFE, LEDU, LINDPRO,
and LAGPOP).
In order to get this done, we have to introduce the variance inflation factor which is also known
as (ViF). The Vif is used mainly to check for the presence of multicollinearity in a regression
model. There is a prerequisite for running this test, The prerequisite is that we must have done
the ordinary pooled ordinary least square (OLS).It is essential to know that the ordinary pooled

57. 47
OLS does not take note of the differences between and within countries which is done in panel
analysis.
Before we can make any comments on the result, we must know the rule of thumb. The rule of
thumb states that if the Vif is less than 5 or when the tolerance 1/Vif is greater that 0.5 then we
can conclude that there is no any form of multicollinearity among the independent variables.
The result is depicted below:
Table 4.2 VIF(Variance Inflation Factor)
Variable VIF 1/VIF
LLFE 2.83 0.353948
LAGPOP 2.46 0.405951
LEDU 2.31 0.432302
LURB 2.19 0.456809
LINDPRO 1.15 0.867146
Mean VIF 2.19
Source: Author’s Compilation from Stata 10.0
It is visible in the above result that there is no linear dependence because Vif is less than 5 for
all the explanatory variables (lURB, lLFE, lEDU, lINDPRO, and lAGPOP). (l means logged
variable)
4.3.2 Test for heteroskedasticity
The concept of heteroskedasticity is known as a violation of the assumption of the linear
classical regression model. It means that there is no constant variance. It is violating the

58. 48
assumption that residual is normally distributed with a mean of zero(0) and constant variance
standard deviation.
So as to check for the presence of heteroskedasticity we have to make use of the groupwise
heteroskedasticity in fixed effects regression. Below is the decision making Criteria:
H0 (null hypothesis) = homoskedasticity exist i.e constant variance
H1 (alternate hypothesis) = heteroskedasticity is present.
The result is shown below:
Table 4.3 Modified Wald test for groupwise heteroskedasticity in Fixed Effect
Regression Model
H0: sigma(i)^2 = sigma^2 for all i
chi2 (22) = 10.59
Prob>chi2 = 0.9802
Source: Author’s Compilation from Stata 10.0
From the above table it is evident that the prob>chi2 is not significant (0.9802), therefore do
not accept H1 that there is heteroskedasticity and we accept H0 that there is homoskedasticity.
Due to this result, there will be no need to robust both fixed and random effects.
4.3.3 Hausman test
This test is used solely to ascertain whether fixed or random effects model is the most
appropriate, preferred and reliable model for the study. It is essential to know that before
running the Hausman test we must ensure that we run and store the fixed and random effects.

59. 49
This test tests if the time invariant variables or unique errors are correlated with the regressors
or not
The decision criteria are listed below:
H0 = the preferred model is random effects
H1 = the preferred model is fixed effects.
Below is the result:
Table 4.4 Hausman test
chi2(5) = (b-B)'[(V_b-V_B)^(-1)](b-B)
= 7.58
Prob>chi2 = 0.1810
Source: Author’s Compilation from Stata 10.0
Since our prob>chi2 is not significant (0.1810), we do not reject H0 and we come to a
conclusion that the random effects model remains the model is the most appropriate, preferred
and reliable model
4.3.4 Interpreting the Random Effects Model
Table 4.5 Random Effects Model
LAGPRO Coef.
Std.
Err. Z P>|z|
[95%
Conf. Interval]
LURB 0.611061 0.213789 2.86 0.004 0.192043 1.03008
LLFE 0.885185 0.638299 1.39 0.166 -0.36586 2.136227

60. 50
LEDU 0.388709 0.175624 2.21 0.027 0.044494 0.732925
LINDPRO 0.086853 0.125884 0.69 0.49 -0.15987 0.333581
lAGPOP -0.08881 0.052198 -1.7 0.089 -0.19111 0.013499
_cons 2.90694 2.810054 1.03 0.301 -2.60066 8.414544
sigma_u 0
sigma_e 0.669941
rho 0
Source: Author’s Compilation from Stata 10.0
The economic interpretation for the random effects model is as follows.
Coefficient Values
For LURB it is 0.611061 which is inelastic. For the variable LLFE is 0.885185 which is also
regarded as inelastic since it is less than 1. The variable LEDU has a coefficient value of
0.388709 which is also inelastic. The variable LINDPRO has a coefficient of 0.86853 which is
also inelastic. The last variable LAGPOP has a coefficient of -0.08881 which is also inelastic.
In conlusion for our coefficient values, all our variables were inelastic which means less than 1
(Coef.<1).
Economic interpretation of the coefficient Values
1 percent change in LURB will bring about a less than proportionate change in LAGPRO. For
the variable LLFE a 1 percent change in LLFE will bring about a less than proportionate
change in LAGPRO. Also a 1 percent change in the variable LEDU will bring about a less than
proportionate change in LAGPRO. A 1 percent change in LINDPRO will bring about a less
than proportionate change in LAGPRO. For the last variable, a 1 percent change in LAGPOP
will bring about a less than proportionate change in LAGPRO.

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Explanation of Z and Probability of Z (P> /Z/)
The rule of thumb is that Z >1.96 means that the variable is significant or it has a significant
influence on the dependent variable. The variable LURB is significant because the value is
more than 1.96. Therefore LURB has a significant influence on LAGPRO. The variable LLFE
is not significant because the value is 1.39 is it is less than 1.96. Therefore we conclude that the
variable LLFE has no significant influence on LAGPRO. The variable LEDU is significant
because it is 2.21 and it is greater than 1.96. we conclude that the variable LEDU has a
significant influence on the dependent variable LAGPRO. The independent variable LINDPRO
is not significant because the value is 0.69 and it is less than 1.96. Therefore we can conclude
that the variable LINDPRO has no significant influence on the dependent variable LAGPRO.
The last variable LAGPOP is also not significant because the value is 1.70 which is less than
1.96. Therefore the independent variable LAGPOP has no significant impact on the dependent
variable LAGPRO.
95% confidence Interval
The rule of thumb is that if the value passes through the number line from -1 to 1 the variable
is not significant. The variable is significant only when the value does not pass through the
number line from -1 to 1.
The first variable which is LURB is significant because zero (0) is not between the intervals.
The second variable LLFE is not significant because zero (0) is between the intervals. LEDU is
significant because the zero (0) is not between the intervals. For LINDPRO it is not significant
because zero (0) is between the intervals. For the last variable LAGPOP, the variable is not
significant too because zero (0) is between the intervals.

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The R-squared
Here will be explaining the r-squared overall. The value is 0.3366. this implies that 33 percent
of variation of the variable LAGPRO is explained by the independent variables.
4.3.5 Testing for Random Effects using the Breush-Pagan Lagrange Multiplier (LM)
Table 4.6 Breusch and Pagan Lagrangian multiplier test for random effects
Test: Var(u) = 0
chi2(1) = 6.31
Prob > chi2 = 0.0120
Source: Author’s Compilation from Stata 10.0
It is evident from the result above that prob>chi2 is significant (0.0120), we reject H0 and we
accept the H1 and we conclude that there is the existence of panel effects. Also there is
evidence of significant differences across countries. Most importantly we can say that the
random effect significantly differs from the simple OLS regression.

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4.4 Summary of findings
The empirical analysis of the effects of urbanization on agricultural productivity in West Africa
presents the result of the significant impact that urbanization level has on agricultural
productivity in West Africa over the period of 1989 to 2010. Based on the results obtained
from the regressions, several things have been noted. Life expectancy at birth was found not to
have a significant impact on agricultural productivity in West Africa. This means that life
expectancy has nothing to do with agricultural productivity. This differed from our a priori
expectation.
For education level which was captured by primary school enrolment was discovered to have a
significant impact on agricultural productivity. This implies that the more educated the people
are, the better will be the level of agricultural productivity. This is in line with our a priori
expectation. Productivity level in the industrial sector was found not to have any form of
significant impact on agricultural productivity. This implies that increase in the productivity
level in the industrial sector will not have any effect on the productivity level in the agricultural
sector. This result differed from our a priori expectation.
Agricultural population, measured by agricultural population (FAO) number was found to have
negative influence on agricultural productivity. Hence, the higher the population of people in
agriculture, agricultural productivity remains unchanged. Interestingly this result did not meet
our a priori expectation. Ideally we believe that if the population of people in agriculture
should increase, the level of agricultural productivity will increase because we will have more
hands in the agricultural sector of the economy. This can be as a result of law of diminishing
returns

64. 54
CONCLUSION
In this section of the study, after estimating the model the results were presented, interpreted
and then discussed. Going by the findings, we can now say that urbanization level has a
positive impact on agricultural productivity in West Africa.

65. 55
CHAPTER FIVE
SUMMARY, RECOMMENDATIONS AND CONCLUSION
5.1 Summary
The main aim of this study was to the determine the effects of urbanization on agricultural
productivity in West Africa for the period of 1989 to 2010. Empirical approach was introduced
to achieve the objectives of the study via the use of cross sectional data using the random
effects GLS econometric method of analysis. The following variables were used in the study
agricultural value added per worker (as the dependent variable), urbanization level, life
expectancy at birth, education level (which was captured by primary school enrolment),
industry value added and agricultural population.
Chapter one of the study focused on the background of the study, the statement of research
problem, the research questions, objectives and hypotheses formulated amongst others. Chapter
two of this study took us through the review of literatures in which several literatures, theories
and empirical papers were reviewed. It was observed that information in extracted literatures
varied and were also findings to be inconsistent on the relationship between urbanization and
agricultural productivity. The third chapter examined the theoretical framework or
methodology used in the study. Then in chapter 4 we estimated the model for the study using
Random effects (GLS) method of estimation. The analysis was carried using data from 14
countries in West Africa

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FINDINGS
Urbanization and industrialization should not be used interchangeably because both are not the
same thing. This is so because some countries urbanized without industrializing. Also the study
discovered from literature that urbanization will increase rapidly in West Africa more than the
way it has increased in the past two decades. Past literatures also presented existing urban
population to be a function of rapid urban population growth. Finally low urbanization
experienced in the past can be attributed to low agricultural productivity. The major empirical
findings of the study are as follows:
i. Urbanization has a significant effect on agricultural productivity in West Africa.
ii. The study also found that there is no significant relationship between life expectancy at
birth and agricultural productivity in West Africa.
iii. Primary school education/enrolment plays a significant role in the growth of
agricultural productivity in West Africa.
iv. The industrial sector has no influence on the agricultural sector of economies in West
Africa.
v. It was also discovered that agricultural productivity is not significantly determined by
the population of people working in the agriculture sector in West Africa.
5.2 Recommendations
Given the findings that urbanization contributes to agricultural productivity positively in West
Africa, it is advisable as a matter of policy, to periodically adjust and monitor the migration of
people from rural to urban areas and vice versa.

67. 57
i. Government should provide mechanized farming instruments for farmers in the rural
areas because most them are in agriculture for subsistence purpose. This is the reason
why the population of people in the agricultural sector does not have a positive impact
on agricultural productivity. If these instruments are made available to farmers in rural
areas then they will be able to compete with major farms and their output will help
increase agricultural productivity in the region.
ii. Structural planning that takes consideration of development in agricultural productivity
should be adopted in creating and classifying urban centers. This must be done because
urbanization is caused by a number of different factors which includes rural-urban
migration and natural increase in population. Also policy makers should endeavor to
formulate policies that will upgrade informal settlements through the provision of
integrated infrastructure and services
iii. Agriculture remains the largest contributor of GDP in most West African countries.
Thus the development of this sector will boost economic output via agricultural
productivity. Also an increase in agricultural productivity will improve the living
standard of the population and should be the main concern of the government. The
government should introduce a strategy to preserve the long term growth of agriculture
in West Africa. Agriculture should be made more attractive for the rural economy so
that people can invest and also work for the progress of their economies.
iv. Policy makers should ensure that they formulate policies that will ensure that more
investments are made in the education sector of West African countries. Since it has a
significant impact on agricultural productivity. This will help increase the literacy level
of the people both in rural and urban areas.

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v. Most importantly policy makers should formulate policies that will encourage
investments in the industrial sector and should overlook the sector. So as to increase the
output of the economy and make the economy more productive. Both sectors will help
increase GDP.
vi. Policy makers should formulate policies that will promote diversification of economic
activities through the creation of new economic hubs in agriculture aimed towards high
value added products and exportation that is sustainable and most importantly inclusive.
5.3 Conclusion
Rapid urbanization has come to stay in West Africa and it will not stop anytime soon. Increase
in Urbanization will affect productivity in the agricultural sector.
This study rejects the null hypothesis that agricultural productivity in West Africa does not
depend on urbanization and also rejects the null hypothesis that there is no positive relationship
between urbanization and agricultural productivity in West Africa. The study concludes that
urbanization level in West Africa has positively affected agricultural productivity.
5.3.1 Limitations of the study
The major limitation experienced in completing this research work is the shortage of research
conducted on this particular subject in West Africa. This research work also encountered the
problem of unavailability and inconsistency of data, due to this Ghana and Niger republic were
dropped.

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5.3.2 Suggestions for further study
During the course of this study, it was noticed that insufficient study was carried out in West
Africa about urbanization and agricultural productivity. West African countries are currently
fast tracked for urbanization most especially the city of Lagos which is on the verge of
becoming a mega city. It is suggested that further studies should be carried out to know the
influence of urbanization on agricultural productivity by using other explanatory variables in
West Africa or sub-Saharan Africa with wider time scope which depends on the availability of
data.

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