i
ABSTRACT
Many researches have been carried out on the impact that population growth have on economic
growth. There is still no clear conclusion on this relationship since some findings indicate that
population growth has a negative impact on economic growth, others indicate a positive impact
of population growth on economic growth. While the linkage between this and change in the
economy is complex phenomenon, some findings have stood to state that, the rate of population
growth have an unpredictable impact on the economy, this study will therefore drew major
attention on the long run consequences of the adjustment in the population growth and the
economy in Kenya. Using time series data on percentage population growth per year and
percentage GDP growth per year from 1960-2010 provided by World bank organization. The
results of this study indicated that population growth and economic growths are both directly
related and that an increase in population will impact positively to the economic growth in the
country. The study also found that there is a sustainable long run equilibrium relationship
between economic growth and population growth. Policy implications of the study are provided.
The study concludes that in Kenya population growth promotes economic growth and
subsequently economic development.
ii
ACRONYMS
LDC – Less Developed Countries
GDP – Gross Domestic Product
USAID – United States Agency for International Development
IMF – International Monetary Fund
WB – World Bank
NPPSD – National Population Policy for Sustainable Development
NCPD – National Council for Population Development
MDG – Millennium Development Goals
ICPD – International Conference on Population Development
USD – United States Dollars
KNBS – Kenya National Bureau of Statistics
SPSS – Statistical Package for Social Sciences
iii
TABLE OF CONTENTS
DECLARATION ................................................................................................ Error! Bookmark not defined.
ACKNOWLEDGEMENT .................................................................................... Error! Bookmark not defined.
ABSTRACT...................................................................................................................................................... ii
ACRONYMS .................................................................................................................................................. iii
CHAPTER ONE: INTRODUCTION .................................................................................................................... 1
1.1. Background of the Study. ................................................................................................................... 1
1.1.1 The GDP growth rate in Kenya ..................................................................................................... 5
1.1.2 Population Programs in Kenya ..................................................................................................... 7
1.1.3 Birthrates in Kenya ....................................................................................................................... 9
1.1.4 Death rates in Kenya .................................................................................................................. 10
1.1.5; Migration of people in Kenya.................................................................................................... 11
1.2. Statement of the problem. .............................................................................................................. 15
1.3. Objective of the study. ..................................................................................................................... 16
1.4. Research Questions ......................................................................................................................... 17
1.5. Significance of the Study .................................................................................................................. 17
1.6. Scope of the Study ........................................................................................................................... 18
1.7. Justification ...................................................................................................................................... 18
1.7.1. Academic Justification .............................................................................................................. 18
1.7.2. Policy Justification ..................................................................................................................... 18
1.8. Limitation of the Study..................................................................................................................... 19
CHAPTER TWO: LITERATURE REVIEW ......................................................................................................... 20
2.0; Introduction ..................................................................................................................................... 20
2.1; Theoretical Literature. ..................................................................................................................... 20
2.1.1 Malthus Model of Population Growth. ...................................................................................... 20
2.1.2 Boserup model of population growth........................................................................................ 21
2.1.3 Anthony Thirwal model of (1993) .............................................................................................. 21
2.1.4 Simon’s Theory of Population Growth ....................................................................................... 22
2.2.4 Solow-Swan economic growth model ....................................................................................... 23
2.1.5 Altruistic models of intergenerational transfers........................................................................ 23
2.1.6 Simon-Steinmann Economic Growth Model: ............................................................................ 24
2.2. Empirical Literature.......................................................................................................................... 25
2.2.1; Impacts of population growth on labor supply and employment ............................................ 25
iv
2.2.2; Effects of slow population growth on economic growth.......................................................... 26
2.2.3; Impacts of population growth on income per capita ............................................................... 27
2.2.4; How demographic factors affect economic growth ................................................................. 27
2.2.5; The relationship between population growth and per capita income ..................................... 27
2.2.6; The relationship between population growth and development ............................................ 28
2.4. Critique of the existing Literature ........................................................................................................ 30
2.5. Research Gaps .................................................................................................................................. 31
2.6. Summary of Literature. .................................................................................................................... 31
2.4 Conceptual framework ..................................................................................................................... 32
CHAPTER THREE: RESEARCH METHODOLOGY ............................................................................................ 34
3.0; Introduction ..................................................................................................................................... 34
3.1. Research Design. .............................................................................................................................. 34
3.2 Model Specification .......................................................................................................................... 34
3.3. Data collection ................................................................................................................................. 35
3.4 Data collection procedure................................................................................................................. 35
3.5 Data processing and analysis ............................................................................................................ 36
CHAPTER FOUR: DATA PRESENTATION AND ANALYSIS .............................................................................. 37
4.1 Introduction ...................................................................................................................................... 37
4.2 The relationship between the birthrates and the GDP..................................................................... 38
4.3; Evaluate the contribution of death rates on GDP............................................................................ 39
4.4: Effects of migration on economic growth ....................................................................................... 41
CHAPTER FIVE: SUMMARY, CONCLUSIONS AND RECOMMENDATIONS. ................................................... 43
5.1: Introduction ..................................................................................................................................... 43
5.2 : Summary ......................................................................................................................................... 43
5.3: Conclusion ........................................................................................................................................ 44
5.4. Policy Recommendations ................................................................................................................. 45
5.5; Contribution to knowledge .............................................................................................................. 46
5.6: Areas for Further Research .............................................................................................................. 46
REFERENCE .............................................................................................................................................. 48
Table of data collected................................................................................................................................ 50
Annex 1; Variables Entered/Removed ........................................................................................................ 52
Annex 2: Model Summary........................................................................................................................... 52
Annex 3: ANOVA ......................................................................................................................................... 52
v
Annex 4: Coefficients .................................................................................................................................. 54
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CHAPTER ONE: INTRODUCTION
This section presents the background of the study, statement of the problem, objectives,
hypothesis, significance of the study, scope of the study, and assumptions of the study.
1.1. Background of the Study.
World population is growing at a high rate and it is becoming a great concern throughout the
world. This is because the population of the world has grown at a very high rate from about 1
billion in around 1800 to around 2.5 billion in 1950 (Martin, 2009).
According to World Bank the world population as at the year 2015 stood at around 7.5 billion
with India and China alone having about 2.5 billion people and this is projected to hit 9 billion
by 2050.
This population growth in some parts of the world is viewed as a real problem while in others it
is considered as a real favor. In recent years, the relationship between population and economy in
developing countries has attracted much attention from different researchers. An observation by
Dawson and Tiffin (1998) shows that "Relationship between population growth and economic
development has long been thought to be fundamental to understanding of less developed
countries (LDCs). Indeed, most textbooks on economic development include a section on
'population and development’."
In most developing countries where the relationship between population growth and economic
performance could be viewed positively, the demographic situation stimulates economic
development which leads to a rise in living standards. This is because in the developing countries
population growth tends to encourage competition in business activities and expanding the
1
potential of the markets. This expansion of the market inspires entrepreneurs to set up new
businesses in order to compete with the already existing ones. A prominent population
economist, Julian Simon, has highlighted the positive side of population growth by noting that a
human being is the vital essential element and “the ultimate resource” that contributes to
economic growth (Simon 1996)
Malthus (1798), in the theory of population trap states that population increases by geometric
progression, while economy grows by arithmetic progression. He further says that at the same
time because of the diminishing to the fixed factors of production e.g. land, food supply would
only be found at an arithmetic rate. Malthus therefore concluded that the only way to avoid this
condition of rapid population growth was for people to engage in moral restraint and limit the
number of their children. Rapid population growth to him put pressure on the existing factors of
production such as land which is fixed in supply. This to Malthus brought about a decrease in
factors of production for all productions that depend on land bringing about various problems to
the human species in terms of food and even at times leading to conflict among beings.
To Bloom and Freeman (1998), food problems that are witnessed in some part of the world are
mainly brought about by high poverty rate and low household income and this is not in any way
related to high rate of population growth as Malthus argued in his theory of population.
Bloom and Canning (2001) on the other hand argued that it is possible for interaction of
demographic transition and economic growth to lead to poverty trap. More recently, Dyson
(2010), supported this by arguing that a decline in the rate of birth by a nation plays a major role
in increasing the standard of living hence people live longer, think more about the future, take
more risk and be more innovative. With this, the economy of the nation will grow faster than
compared to an economy with high birth rate. A decline in mortality accompanying good
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standard of living by a healthy society would, in turn, boost the individual productivity. (Straus
and Thomas, 1998).
Rapid population depress the saving by the households and the capital held by the workers. The
government must also increase the public expenditure on the provision of social infrastructure
and meet the needs of the additional population. There is also more pressure exerted on the
balance of payment as a result of the need to import food and development of new industries to
expand the country’s exports in substitution for the food imports. Pressure is also put on the
available resources such education and facilities which may result in poor education and health;
which are the main problem in developing economies as they result to pressure on employment
and amount of capital available for investment (Martin, 2009).
The relationship between population growth and economic performance in a country is regarded
as a negative phenomenon if the increase becomes a barrier to the country's economic
development. This is as a result of the dependency burden (the part of the population who are
economically unproductive such as children and elderly) caused by the rapid population growth.
Julian Simon in Simon (1996) has highlighted the positive accompaniments of population growth
by noting that a person is a very important element and a 'resource' contributing greatly to
economic growth.
A high population may mean a high production and a high consumption resulting to economic
growth. This can only be witnessed when employment opportunities grow faster and people
acquire the required standard of education. A large population is also a greater source of market
for the produced goods and the zero-population growth is not suitable for a country that requires
a sustainable economic growth (Gerald and Meier, 1995).
3
Kenya is one of the largest countries in Sub-Saharan Africa with a population of about 44
Million, 29th worldwide and the population is growing at a rate of about 27% annually. This
population is expected to reach about 50 million by 2050 (United Nations, 2015).
The main natural resources in Kenya are wildlife, soda ash, and land with most emphasis given
to agriculture making it the highest contributor of exports in the country. (Bureau of African
Affairs, 2010).
Although Kenya is in the growth stage, there are many factors that still inhibit the level of
growth in the country and contributing to poverty trap making about twenty percent of the
Kenyans to live on less than a dollar a day, and half of the population to live below poverty.
(African Outlook 2010). The trend in population growth in Kenya has been fluctuated over time.
According to Republic of Kenya (2010), the Kenyan population recorded the highest growth rate
of about 4.7 percent in 1967 with a great increase witnessed in 1979 from 3.3 to 3.8 between
1969 and 1979.
Kenya in the 1970s was named among one of the countries with high population growth in the
world, with high level of fertility in the country contributing more than any other demographic
event. (IMF, 2010). This prompted the government to encourage the use of family planning in
the families to lower fertility in the households as it was resulting to slow economic growth in
the country making Kenya one of the first African countries to adopt the family planning policy
(Ajayi and Kavole,1998). The promotion of the family planning policy by the government yield
fruit as the fertility rate dropped from about 8 children per woman in mid-1970s to 5.4 in the
early 90s. (NCPD et al., 1999). The use of the family planning has since increased in Kenya with
about 46% of the married women having used in once in their marriage life (Kenya National
Bureau of Statistics, 2009).
4
According to United States Agency for International Development (USAID) 2009 report, Kenya
needs to put a check on the rate of growth of the population as this may hinder growth in the
economy. Kenyan population growth rate needs to be reduced from the current three percent to at
least a third. (Anyangu-Amu, 2010. This comes despite the fact that Kenya has transformed so
much in recent years from agricultural based economy to service based but agriculture still
comes ahead of other sectors by a 25% contribution to GDP. (Wanjala and Were, 2009)
1.1.1 The GDP growth rate in Kenya
Kenyan economy has experienced many booms and bust in its economy testing the environment
and political stability in the country. Rapid economic growth in Kenya was seen between 1964
and 1973 when the country endured a growth rate of 6.6 percent. This growth, however, did not
last any longer since in 1994 Kenya went through a period of economic stagnation and crisis
resulting to pressure from lenders such as IMF and World Bank to comply with the Bretton
Woods project. By 2003 Kenya had reached recovery and the economy recorded an increased
growth rate (Little and Green, 2009).
According to Bureau of African Affairs, (2010), the 2007 presidential post-election violence
which resulted in over 1000 deaths and displacement of about 300,000 people, Kenya witnessed
a great economic hardship including increased unemployment, reduced balance of payment and a
reduction in investor confidence. The suppression of investor confidence due the post-election
violence led to a decrease in the number of foreign investors in the Kenyan Stock Market to as
low as 2500 points in mid-2009. (World Bank 2010).
The prolonged post-election violence, inconsistent rainfall amount, and global economic
recession witnessed resulted to high inflation and weak currency causing a slow growth in the
economy in 2010. (IMF, 2010).
5
With the introduction of the Kenyan Vision 2030 in 2008 by the government to fund various
investment growths through an increase of credit supply to the private sector and public sector
infrastructural investment, the economy made a great step forward towards recovery. The
strategy has since helped the economy to recover by contributing to a GDP growth of about 2.6
percent in 2008 and this is expected to push the economy further. (African Economic Outlook,
2008; pg. 34).
The trend in population growth in Kenya has been fluctuating over the years from 1960 to 2014.
The figure 1.1 below extracted from World Bank shows that the country recorded the highest
population growth in 1967 at 3.9 percent. The highest growth rate was witnessed between 1969
and 1979 with a population growth rate of 3.4 to 3.8 percent. Between 1979 and 1989 the
population growth dropped from 3.8 to 3.5 percent. In 1999 population growth dropped further
to a 2.5 percent growth but a little growth was seen in 2009 with an increase from 2.5 percent to
2.6 percent an increase of 0.1 percent. -10
6
Figure 1.1 Trends in GDP growth and population growth over the period 1960-2010
Source: World Bank 7
1.1.2 Population Programs in Kenya
Since attaining political independence, the government has prioritized the improvement of the
health status of Kenyans. The government recognizes that good health is a prerequisite to socioeconomic development. A number of government policy documents and successive national
development plans have stated that the provision of health services should meet the basic needs
of the population, place health services within easy reach of Kenyans, and emphasize preventive,
promotive, and rehabilitative services without ignoring curative services. Perhaps as a result of
these policies, both infant mortality and life expectancy at birth, which are basic indicators of
health status, have improved significantly (Ngigi and Macharia, 2006).
7
Kenya was the first Sub-Saharan African country to have a population policy by forming of the
National Family Planning Programme to reduce population growth in 1967. However, the
implementation of the population policy did not yield the desired results and led to the revision
of the 1967 policy to form the Sessional Paper No. 4, of 1984 on Population Policy (Muia et.al
2003). The 1984 policy incorporated demographic and socio-economic goals and diversified
implementing ministries and non-governmental and religious organizations. The demographic
intentions in the Sessional paper were to reduce the population growth rate, reduction of fertility,
reduction of mortality particularly infant and child mortality and also the reduction of rural–
urban and rural–rural migration.
In 2000, the government of Kenya launched the National Population Policy for Sustainable
Development (National Council for Population and Development, 2000). This policy builds on
the strength of Kenya’s first national population policy outlined in Sessional Paper No. 4 of 1984
on Population Policy Guidelines. The policy outlined ways to implement the programme of
action developed at the 1994 International Conference on Population and Development in Cairo,
Egypt. The policy also addressed the issues of environment, gender, and poverty, as well as the
problems facing certain segments of the Kenyan population, such as its youth. Among the salient
features of these policy included improvement of the standard of living and quality of life,
improvement of the health and welfare of the people through provision of information and
education on how to prevent illness and premature deaths among risk groups, especially among
mothers and children, sustenance of the ongoing demographic transition to further reduce
fertility and mortality, especially infant and child mortality, continuing motivation and
encouragement of Kenyans to adhere to responsible parenthood and sustainability of the
population programme among others.
8
Under the long-term development of vision 2030 the Kenyan government through the National
Coordinating Agency for Population and Development, has initiated a review of the National
Population Policy for Sustainable Development. This review is aimed at updating the said policy
blueprint, whose implementation period ended in December 2010. The review aims at aligning
the population policy, strategies and programs with the Millennium Development Goals
(MDGs), and Kenya Vision 2030. It also seeks to incorporate the newly emerging population
issues within the development framework.
Owing to its high fertility and declining mortality, Kenya is characterized by a youthful
population. Projections show about 43 percent of the population is younger than 15 years
(Republic of Kenya, 2009). This implies that over three-fifths of Kenya’s population, or about 25
million people in 2009, are less than 25 years old. Consequently, Kenya faces the formidable
challenge of providing its youth with opportunities for a safe, healthy, and economically
productive future. The 1994 International Conference on Population and Development (ICPD)
endorsed the right of adolescents and young adults to obtain the highest levels of health care. In
line with the ICPD recommendations, Kenya has put in place an Adolescent Reproductive Health
and Development policy (ARH&D) (Odini, 2008).
1.1.3 Birthrates in Kenya
The value of birth rate for Kenya was 31.8 per 1,000 people by the year 2010. Birth rate of
Kenya fell gradually from 50.7 per 1,000 people in 1960s to 31.8 per 1,000 people by 2010.
Definition: Birth rate indicates the number of live births occurring during the year, per 1,000
population estimated at the end of the year. Subtracting the death rate from the birth rate
provides the rate of natural increase, which is equal to the rate of population change in the
absence of migration. The number of birth rates in Kenya from 1960-2010 is as shown in the
9
graph below indicating a decreasing in the number of births from 1960 all the way to 2010.the
number of births in 1960s was very high probably due to lack of family planning programmes
which were not in effect by then.
Fig 1.2 Number of births per 1000 people from 1960-2010
1.1.4 Death rates in Kenya
The value for Death rate (per 1,000 people) in Kenya was 5.94 as of 2010. As the graph below
shows, over the past 50 years this indicator reached a maximum value of 20.21 in 1960 and a
minimum value of 5.94 in 2010.
Definition: Death rate; it refers to the number of deaths occurring during the year, per 1,000 of
population estimated per year. Subtracting the death rate from the birth rate provides the rate of
natural increase, which is equal to the rate of population change in the absence of migration.
10
Fig 1.3 Number of deaths per 1000 people from 1960-2010
1.1.5; Migration of people in Kenya
Refugees and stateless persons
Kenya hosts one of the largest refugee populations in Africa. There are two main camps:
Kakuma refugee camp; and Dadaab refugee camp, which is a complex of five camps and is the
largest refugee camp in the world as well as one of the oldest. As of 31 March 2010, the
estimated population of Dadaab and Kakuma refugee camps is 351,446 and 181,821
respectively. The population of the Dadaab camps has decreased in recent years. The main
countries of origin for refugees in Dadaab camp are Somalia and Ethiopia. In less than four
years, the population of Kakuma has grown more than two-fold. The vast majority of the
Kakuma camp population is from South Sudan. There is also an urban refugee and asylumseeker population based in Nairobi approximately 52,957 as of 31 March 2010. The majority of
this urban refugee population is from Somalia, followed by refugees from Ethiopia, the
11
Democratic Republic of the Congo, Eritrea, and others. Overall, approximately 72 per cent of the
refugee population in Kenya is from Somalia, followed by South Sudan (16%), Ethiopia(5%), .
Resettlement numbers from Kenya have varied over time; with higher numbers in 2009–2010
(10,904 - 9,878 respectively).
There are currently an estimated 20,000 stateless persons in Kenya, including Kenyan Somalis
and Kenyan Nubians.
Migration and demographics
As of the 2009 census, Kenya’s population was 38.6 million. It is steadily growing, with
projections that it will reach over 50 million by 2020. Population growth is mainly due to natural
increase. Young people between the ages of 15 and39 account for 35.4 per cent of the
population, representing a large pool of potential domestic and international migrants. Kenya
experiences net emigration as departures of the citizens exceeds arrivals of foreigners.
Migration and economic development
The Kenyan diaspora is a major contributor to the economy of the country. The Central Bank of
Kenya regularly reports on the remittances received in Kenya from diaspora abroad, based on
information provided by money transfer organizations. According to this data in 2010, over 1.4
billion USD was remitted to Kenya. This figure is likely to be low given that there are other,
informal means of remitting monies to Kenya. The main sources of these remittances were
diaspora in North America (55%) and Europe (27%). Recipients of remittances Migration in
Kenya: A Country Profile 2010 19use the funds mostly for food purchases, homes (including
construction, rental, and renovations), education, land purchases, and health, with fewer using
the money for business or investments. Foreign direct investment and tourism have been key
contributors to economic development. Foreign direct investment has risen steadily over the past
12
three decades, reaching USD 335 million in 2010. In recent years there has been some instability
in foreign direct investment, possibly as a result of recent instability in the country, but also
likely due to corruption, crime, theft, problems with contract enforcement, inadequate
infrastructure, and inadequate protections for investors. The direct contribution of tourism to
gross domestic product was 5.7 per cent in 2010; however, the numbers of arriving tourists have
decreased in recent years as a result of terrorism and the Ebola outbreak in West Africa.
Domestic remittances have helped drive demand for mobile money providers in Kenya.
Migration policy framework
There are four key policy documents relevant to migration: Kenya Vision 2030, the National
Migration Policy, the National Labor Migration Policy, and the National Diaspora Policy. The
Kenya Vision 2030 is the Government of Kenya’s national planning strategy, and is
implemented through a series of five-year Medium Term Plans. The overall vision of Kenya
2030 is to “transport Kenya into a newly industrializing, middle-income country providing a high
quality of life to all its citizens by the year 2030” through three pillars: economic, social, and
political. Minor references are made to migration in Vision 2030, but it does not adequately
mainstream migration as a potential contributor to national development. The National Migration
Policy remains in draft form, as does the National Labor Migration Policy.The foreign national
population in Kenya has increased between 1990 and 2010. Table 3 details the international
migrant stock in Kenya at five-year intervals.
13
Table 1.1: Trends in international migrant stock in Kenya, 1990–2010
INDICATOR
1990
1995
2000
2005
2010
Estimated number of international
migrants at mid-year
162,981
527,821
755,351
790,071
790,071
Estimated number of refugees at midyear
13, 452
243,544
214,901
245,553
269,130
Population of Kenya at mid-year
23,433
27,492
31,441
35,817
40,863
Estimated number of female migrants
at mid-year
79,850
261,796
379,281
401,620
415,688
Estimated number of male migrants at
83,131
266,025
376,070
388,451
402,059
International migrants as percentage
of the population
0.7
1.9
2.4
2.2
2.0
Female migrants as percentage of all
international migrants
49.0
49.6
50.2
50.8
50.8
Refugees as percentage of
international migrants
8.3
46.1
28.5
31.1
32.9
(thousands)
mid-year
Kenyan emigrant population
Estimations of the size and distribution of the Kenyan diaspora vary. According to the Kenya
Diaspora Policy, “the number of Kenyans abroad is estimated to be about three million and is
continuously on the rise” (MFAIT, 2014a:8). In 2011, the World Bank’s Migration and
Remittances Factbook estimated that Kenya’s diaspora population in 2010 reached 457,000
individuals. The report identifies the Uganda-Kenya border as a top migration corridor in subSaharan Africa and found that the United Kingdom is the top destination for Kenyan emigrants,
followed by the United Republic of Tanzania and the United States (Canuto andRatha, 2011).
McCabe (2011) provides a conservative estimate of the Kenyan emigrant population at 87,267,
or 5.8 per cent of the African emigrant population in the United States, making it the fifth largest
14
African diaspora community after Nigeria, Ethiopia, Egypt and Ghana. Kinuthia’s study (2013)
showed the distribution of Kenyans across the globe from 1960 to 2010 using the World Bank
Migration Data (1960–2010) and the Global Migrant Origin Database of 2007 (Table 26). The
largest share of Kenyan emigrants has, since the 1960s, been located within Africa, as outlined in
the table below.
Table 1.2: Geographical distribution of the Kenyan diaspora
REGION
1960
1970
1980
1990
2000
2010
Africa
54,245 84,506
94,683
104,773 538,128 876,695
Asia (Including China, India
and the Middle East)
3,678
38,608
30,830
21,801
966
92,731
Europe (including Eastern
Europe)
788
30,834
22,367
23,678
920
70,674
Americas (including Latin
America)
302
4,006
6,299
8,762
161
19,329
Caribbean
35
163
768
1,431
21
2,496
Australia and New
216
427
226
0
6
849
Pacific
11
25
12
0
0
262
TOTAL
59,275 158,569 155,185 149,445 540,202 1,063,036
Zealand
1.2. Statement of the problem.
There is continued divergence of opinions regarding the consequences of population growth on
economic growth. The debate between positive impact and negative impact of population growth
on the economy is thus still ongoing. On the positive side, economist argues that population
growth induces technological advancements and innovations. This is because population growth
encourages competition in business activities and, as the country’s population grows, the size of
15
its potential market expands as well. The expansion of the market, in its turn, encourages
entrepreneurs to set up new businesses.
A large population growth on the other side is not only associated with food problem but also
imposes constraints on the development of savings, foreign exchange and human resources. The
increase in demand for food leads to a decrease in natural resources, which are needed for a
nation to survive. Other negative effects of population growth include poverty caused by low
income per capita, famine, and disease since rapid population growth complicates the task of
providing and maintaining the infrastructure, education and health care needed in modern
economies. The third school of thought is that population growth is a neutral factor in economic
growth and is determined outside standard growth models (Felmingham, 2004).
Cross national evidence on the relationship between population growth and economic growth is
inconsistent because the underlying parameters and assumptions vary across countries. The
existing literature also points out that depending on the country; population growth may
contribute, deter or even have no impact on economic growth. Hence, there is the need to
eliminate the divergent views by determining the effect of the total population, population
growth, and population density on economic growth.
1.3. Objective of the study.
The general goal of this study is to assess the impact population growth on economic growth in
Kenya.
Specific objectives of the study include;
•
To determine the relationship between the birthrate and economic growth in Kenya.
•
To evaluate the contribution of death rates on economic growth in Kenya.
16
•
To examine the effect of migration on economic growth in Kenya.
1.4. Research Questions
The following are the research questions that emerged as a result of different findings by
different studies
•
What is the relationship between the birthrates influence economic growth in Kenya?
•
How does the death rates contribute to the economic growth in Kenya?
•
What are the effects migration on economic growth in Kenya?
1.5. Significance of the Study
This study is very important especially to the policy makers as it will provide ways on how to
make great economic benefits from the annual growing population in Kenya.
The study will be significant in the following ways;
a) It will help the policy makers and the government to come up with various policies to
create employment for the growing population.
b) It will also have an implication for coming up with a formula to distribute resources
evenly.
c) This study will also be of great benefit to the students studying economics and other
related disciplines who want to make further research on the same subject.
d) The study will help the government to come up with the policies on how to control
mortality rate in the country.
e) The study will also help the government to solve the problem of immigration along its
borders.
f) The study will also enrich the already existing literature review.
17
1.6. Scope of the Study
The study will cover the impact of population growth on the growth of the economy in Kenya for
the period between 1960 and 2014. The study will employ the use of estimated population rate of
growth and the economic rate of growth.
1.7. Justification
1.7.1. Academic Justification
This research will be an addition to the already existing literature works on the impacts of
population growth on economic growth in Kenya. The findings can then be utilized by future
researchers and academicians as they carry out their own literacy works.
1.7.2. Policy Justification
Kenya’s economic and population growth and well-being today and also in future needs stability
of the economy which is the government’s main concern and responsibility to provide it and also
ensure its continuity. The government has in the past and current times been grappling with the
high rate of population growth mainly brought about by the increasing fertility and high growth
of urban centers. However, the measures being employed so far to tackle this increasing
population have proved to be disappointing and at times inefficient since some of them cannot be
accessed by the low-income earners. Achieving a lasting solution and various ways to provide to
the already high population is essential yet uphill task for not only Kenya’s government but also
in other parts of the world, but it could be rendered meaningless within a very short period of
time if the government does no regulate or come up with policies to control the high growth in
population mishaps.
18
1.8. Limitation of the Study
The following are the problems that will be encountered during the study which may affect the
findings.
•
Limited access to literature. Some journals and publications which could have been of
great help during the study and research were not accessible.
•
The use of secondary data which are mostly estimates and do not give the actual picture
on the ground.
•
An absence of some crucial data which would have acted as a major boost to the findings
of the research.
•
Due to the Solow model, the investment rate has a vast effect on the economic growth.
However, because of the shortage of data and time investment rate data cannot be
included in the regression model test.
Moreover, we also assume that other variables do not affect much on the result of our regression
test.
19
CHAPTER TWO: LITERATURE REVIEW
2.0; Introduction
This chapter examines the literature reviews in relation to this research which include; theoretical
review, empirical literature, conceptual framework and the summary of the literature review. The
critiques and research gaps are also discussed.
2.1; Theoretical Literature.
According to Luigi et al. (2010), the various schools of thoughts regarding the relationship
between population growth and economic growth can be grouped into three main classifications.
The grouping depends on their results on the evaluation of the effect population growth has on
economic progression. The first class is that which found a negative relationship between
population rate of growth and the economic growth, the second category is those that found a
positive correlation between population growth and economic growth and the last category is
that of those that found no significant impact of population on the economy.
2.1.1 Malthus Model of Population Growth.
Malthus was an English economist and demographer and he is the first negative theorist well
known. In his book Essay on the Principle of Population (1798), Malthus argued that rapid
population growth leads to a decrease in the per capita output because economic growth cannot
keep up with the rate at which the population grows. He further argued that population grows at a
geometric rate while the Gross Domestic Product (GDP) grows arithmetically to mean that
population could double after every 25years. Malthus advocated for various measure to keep the
population in check and he was known for famous quote “The superior power of population
cannot be checked without producing misery or vice”.
20
He argued that two types of checks hold population within resource limits these checks are the
positive checks, which are aimed at raising the death rate; and preventive checks, which on the
other hand are geared towards lowering the birth rate. The positive checks include hunger,
disease and war; the preventive checks he advocated for were; abortion, birth control,
prostitution, postponement of marriage and celibacy.
2.1.2 Boserup model of population growth
Boserup (1965) found out that population growth is an autonomous factor, which affects
agricultural productivity rather than being affected by it, as suggested by the Malthusian school.
The study claimed that Malthus' assumption of diminishing returns to labor needs not hold in the
long run, as higher population may lead to a more efficient division of labor as well as to
improved agricultural practices (signaled by the frequency of cropping). The study concluded
that soil fertility should not be viewed as fixed and given by nature, but instead can be improved
by substituting the agricultural technology to a better one, which is likely to be a result of an
increase in population. Primitive communities with higher population growth rates are more
likely to experience economic development, provided that the necessary investment in
agriculture are undertaken.
2.1.3 Anthony Thirwal model of (1993)
Thirlwal (1993) investigated the relationship between population growth and economic
development with special reference to developing economies. The study found out that the
relationship between population growth and economic development is a complex one,
particularly concerning what the cause is and what the effect is. Rapid population growth lowers
per capita income growth in least developed countries (LDCs), yet there are many ways in which
population growth may be a stimulus to progress, and there are many rational reasons why
21
families in developing countries choose to have many children. The study concluded that
complexity of the subject is compounded by the fact that, economic development is a
multidimensional concept. The pace of economic development depends on the diversion of
resources from consumption to uses that raise future output. A population with a high ratio of
dependents on producers consumes more of a given output and devotes less to investments.
Thus, high fertility, which produces a high level of dependency, promotes consumption at the
expense of investment.
2.1.4 Simon’s Theory of Population Growth
Simon (1977) investigated the long run benefits of population growth. Whereas population
growth has a negative effect on living standards in the short run due to diminishing returns and
the temporary burden it poses on society, it has positive effects on living standards in the long
run due to knowledge advances e.g innovation and economies of scale. Employing a simulation
model, the study found out that in the long run (after 30 to 100 years) and when compared to
constant-size population, moderate population growth improves standards of livings both in more
developed and in less developed countries. In the long run, a growing population tends to
advance knowledge, which, in turn, increases productivity and output at a higher rate than that of
population growth. Nevertheless, a country's optimal policy regarding population growth
depends on the weight given to future periods relative to the present. The more weight a country
gives to future generations and the more willing a country is for the short run decline in
standards of livings, the better it is for that country to pursue a policy of moderate population
growth. The long run benefits of population growth that links to economic growth of poor
countries are on the positive balance, contrary to conventional wisdom.
22
2.2.4 Solow-Swan economic growth model
Porter et al. (1996) employed a Solow-Swan economic growth model with exogenous saving
rates to determine the relationship between population growth and economic growth. The model
assumed that both the saving rate and the consumption rate are given. Taking a household owns
the input and manages the technology. The production technology is assumed to take the form
Y = F (K, L),
(2.1)
Where Y is total output,
K is total physical capital,
And L is the size of the labor input
The production function exhibits positive and diminishing marginal products with respect to each
input and also exhibits constant returns to scale. The economy is assumed to be a one-sector
economy, where output can be either consumed or invested and capital depreciates at a constant
positive rate. The growth rate of population is exogenous. The model further assumes that this
growth rate is a constant (n) and that labor supply per person is given. Normalizing the
population size at time zero and the work intensity to one yield the following is the labor input.
Defining a steady state as a situation in which the quantities, such as capital, population, and
output, grow at constant rates. In the Solow-Swan model a steady state exists if the net increase
in per capita capital is equal to zero.
2.1.5 Altruistic models of intergenerational transfers
Becker et al. (1999) in the study of the consumption behavior of people considered the behavior
of people as being guided by the utility gained and that of their offspring. The utility of the
23
children depended on the parents’ utility and the chain continues. For that reason, the current
generation would consume without affecting the utility that would be achieved by their offspring.
Through this inter-linking chain, the current generation consumes and transfers resources to its
children influenced by its concern not only for its own children but for all future generations. An
important implication of this model is that familial transfers will neutralize fiscal policy. When a
government exercises expansionary fiscal policy it stimulates the economy by increasing current
spending financed by issuing debt. From the perspective of intergenerational transfers, the policy
is an effort to stimulate spending by transferring resources to current generations from future
generations. According to this model however, the public policy is undone by altruistic
households. They compensate future generations by increasing their saving and accumulating
wealth, exactly offsetting the increase in public debt. This model implies that public
intergenerational transfers and private intergenerational transfers are perfect substitutes. A
change in public transfers is matched dollar for dollar by a compensating change in private
transfers.
2.1.6 Simon-Steinmann Economic Growth Model:
The basic idea to the theory proposed by Julian Simon and Gunter Steinmann is that the greater
the total population, the greater the level of technological growth, larger markets, increased
production thereby yielding the greater the per capita income in the economy. An idea derived
from Boserup (Simon 1977), which Simon refers to as the ―Population Push model and
distinguishes between current knowledge and knowledge being applied for production.
Underlying the population push model of technological development is the added idea that
technology can and does develop independent of population growth (learning-by-doing) and
therefore technology builds upon itself, reconciling the pull and push models of technological
24
progress. So even in the case of a static population, there will be some level of technological
advancement, albeit slower than in situations of growing population. It is just necessity remains
the mother to, and is the primary force behind, invention. This technological progress function is
added to the Douglas-Cobb production function to produce a model containing endogenous
technological progress based on population growth and learning-by-doing. One other aspect of
note in his model is that birthrates and population are used synonymously as he dismisses the
impact of age-structure and dependency ratio on economic growth as minimal to the effect of the
savings rate. He uses Japan and the US as an example of the disparity between savings rate and
the effect it has on output (Simon 1977). The results of the model yield modest per capita
economic growth at equilibrium and Simon determines that maximized long term economic
growth (always in per capita terms unless otherwise noted) requires 1-2% per annum population
growth and a 2-4% rate of savings with a low discount rate below 4%. At a higher discount rate
of 5-10% there was still increased consumption. This population growth rate, he makes clear, is
higher than the rate that produces the highest adoption of technology (Simon 1986). Any growth
that occurs too fast will have diminishing return or create a circumstance where it is stagnating.
As well, modest negative population growth will have the effect of limiting growth but large
negative out flows in population will stagnate growth outright. The level of total technology
(available and in use) never decreases since this is, in his estimation, illogical. (Simon 1986).
2.2. Empirical Literature
2.2.1; Impacts of population growth on labor supply and employment
Bloom and Freeman (1986) provided a comprehensive organizing framework for analyzing the
impact of population growth on labor supply and employment. In particular, they identified two
distinct mechanisms through which population growth affects labor supply and employment.
25
One is the "accounting" aspect that refers to changes in the demographic structure and cohort
size. The other is the "behavioral" aspect that refers to the decision to participate in the labor
force, particularly for women. Fertility, mortality and migration will affect labor supply
differently. Mortality and migration will have immediate effects while fertility will have delayed
effects. They also pointed out that the structure of the labor market mediates the impact of
population growth on employment. For instance, in a neoclassical labor market rapid population
growth will instantaneously depress wages. In a dual labor market where one market (modern) is
behaving like a new classical labor market and another (traditional) is characterized by surplus
labor and low wage rates, rapid population growth will delay the tightening of and eventual
dissolution of the low wage traditional labor market (or the elimination of the dualistic structure).
In their review of labor markets in developing countries covering the period 1960-80, they
concluded that despite population increasing rapidly, developing countries managed, on the
whole, to improve their economic positions significantly.
2.2.2; Effects of slow population growth on economic growth
According to Kelley (1988) a lower the pace of population growth will help to enhance
economic growth at a higher rate. The study elaborated that economic growth would be higher in
the situation of slower population growth even though the impact of population growth in many
countries was insignificant. Population and per capita income are closely associated to depict the
picture of economic growth. Lower the population growth and higher the per capita income show
that nation achieve their growth targets. Countries with population growth under 1 percent, their
per capita income could increase at the rate of 2.5 percent annually. Countries with population
growth more than 2 percent had a little increase in per capita income of less than 2 percent.
26
2.2.3; Impacts of population growth on income per capita
Wenig and Zimmrman (2012) used a Cobb-Douglas economy-wide production function to
investigate the impact of population growth on ‘steady state’ income per capita as well as on
economic growth in the transition to the steady state. They revealed out that an increase in the
population growth rate of 10% (e.g. 3% to 3.3%) would reduce per capita income in the steady
state by 5%. If, however, one considered human capital to be an additional factor of production
(which is eminently reasonable), then the negative impact of population growth is larger as
population growth now forces economies to use their scarce savings to equip young people with
physical and human capital. As a result, a 1% increase in population growth would decrease per
capita income by 2%.
2.2.4; How demographic factors affect economic growth
Bloom and Williamson (1997) also found that demographic factors are important determinants of
economic growth. Their results show that it is not overall population growth rate that drives
economic performance but age distribution. The age distribution effect operates through the
difference in growth rates of the working-age and the dependent population. The study found
that population dynamics explain as much as 1.4 to 1.9 percentage points of the GDP per capita
growth in East Asia or as much as one third of the average East Asian miracle GDP per capita
growth rate (1.9/6.1). In Southeast Asia, the estimated effect ranges from 0.9 to 1.8 points of
economic growth or about half (1.8/3.8) of the recorded growth in GDP per capita.
2.2.5; The relationship between population growth and per capita income
Bucci (2003) investigated whether there is a long-run relationship between population (size and
growth) and per-capita income focusing on human and physical capital as reproducible inputs.
The study found out that population growth exerts a negative effect on economic growth.
27
However, when individuals choose endogenously how much to save, population growth can also
have a neutral influence on economic growth. The study also extended its analysis to the case
where physical and human capital can interact with each other in the production of new human
capital. When the two types of capital are substitutes for each other in the education sector, the
effect of population growth on per-capita income growth is always negative. Instead, if human
and physical capital is complementary for each other, the impact of population change on real
per-capita income growth becomes ambiguous. The intuition is the following. For given percapita physical capital stock, an increase of population causes the aggregate physical capital to
rise. If physical and human capital are substitutes for each other (in the sense that the larger
amount of physical capital now available in the economy deters the demand and, thus, the
consequent supply of human capital), the increase of population size, together with the reduction
of the aggregate human capital stock, determines an unambiguous decline of the per-capita level
of skills and, via this channel, a lower per-capita income growth rate. On the other hand, if
physical and human capital are complementary for each other (the increase in the supply of
physical capital spurs the demand and, therefore, the consequent production of new human
capital), the final effect on the per-capita level of skills and, hence, on per-capita income growth
of an increase in population may be either positive, or negative, or else equal to zero. Long-run
per-capita income growth can be positive even without any population change; in equilibrium,
both the growth rate and the level of per-capita income are independent of population size; the
long-run level of per-capita income is proportional to per-capita human capital.
2.2.6; The relationship between population growth and development
Kuznets (1967), is the he best known early analysis of the relationship between population
growth and development. In his study, he found a positive correlation between population
28
growth rates and income per capita within broad country groupings, this, he interpreted as
evidence of a lack of a negative causal effect of population growth on income growth, contrary
to the view that was prevailing at the time.
The various researchers that followed Kuznet in the study of the same subject have come up with
different findings on the relationship between population growth and the income growth. Kelley
(1988), found no correlation between population growth and growth of income per capita, and
similarly no relationship between population growth and saving rates. In his summary of other
numerous studies, in his view, the evidence that were there to support the negative effect of
population growth on economic development did not exist or were very weak. Kelley and
Schmidt (2005) regression of the rate of growth of income per capita on the growth rates of the
population and the working-age population, incorporating both Solow effects (a decrease in the
capital stock with an increase in the number of workers) and the various effects of dependency,
explains approximately an average of 20 percent of the growth of income per capita in the period
between 1960 and 1995. Acemoglu and Johnson (2007) on the other hand conclude that a higher
population growth has a negative significant effect on GDP per capita at a possibility of several
decades.
Bloom et al. (2009), in their study using abortion legislation as an instrument as well as a
negative impact of fertility on female labor force participation conclude that the extra labor
supply would be a significant channel through which lower fertility would raise income growth,
although they mention that saving and human capital accumulation are expected to be important
channels as well.
29
2.4. Critique of the existing Literature
Malthus’ theory argued that there was diminishing return when it comes to scarce resource like
food and water while some of optimistic ”population growth” economists, like Kuznets (1956),
Boserup(1965) and Simon (1981), believed that population growth can is very essential factor in
moving the economy from a less effective one to an economics of scale economy as said by
Kendrick (1977) that economies of scale are helps a country to attain high productivity by
increase in output per unit of labor of one nation.
Regardless of the sufferings faced by countries as a result of the increasing population such as
capital dilution, shortage of necessity resources and the casualty which may result to severe
poverty for the entire population, famine and even starvation., there are two arguments supported
for the idea that population growth can boost the country economy by “economies of scale”
phenomenon. A country, which has a rapid population growth;
Firstly, the larger the population size is, the larger the market size for good and services
produced in a nation hence the improvement growth in the economy of a nation. Nevertheless, in
order to meet the product demand of the large-size market, bigger and more effective as well as
longer performance period manufacturing plants are required to develop to ensure there is
continuity in supply of goods and services in the economy.
Secondly, despite the large size market created by the high population the economy also
possesses an impressive number of labors which is available when need be. This availability of
labor force makes it possible for firms to divide their labor into various sectors to perform
specific tasks resulting to labor efficiency and increased output.
30
2.5. Research Gaps
There have been various views on the whether population growth actually has an influence in the
level of economic growth. Most of the analyzed research work pointed to the position that there
are varying theories that support that population increases the level of economic growth while
others are countering this idea. Due to this, there is still no clear conclusion in this subject
providing clear room for this study.
2.6. Summary of Literature.
Many researcher and demographers have come up with various theories concerning the impact
that population growth have on the GDP growth (economic growth) in various economies. The
theories and the research findings can be divided into three different categories. First category
comprises of the belief that population growth has a positive impact on the growth of the
economy this category includes Malthusian theory of population growth that rapid population
growth result to diminishing returns on resources and Simon who found a negative relationship
between population growth and economic growth Acemoglu and Johnson who concluded that
growth in population contributes negatively on GDP per capita. The second category is that of
the believers in the positive contribution of population growth on the economic growth, the
category includes the theory by Bosserup who claimed that population growth results to
efficiency in the division of labor as well as improved technology in agricultural production.
Finally, the last category is made of those who believed that population growth has no significant
impact on the growth of the economy they include, Kuznet who evidence of a lack of a negative
causal effect of population growth on income growth, contrary to the view that was prevailing at
the time.
31
Generally, most of the research done on population and its relationship with economic growth
had limitations because of data used, namely cross-sectional country data on one particular time,
not time series data over a long period. Based on cross cross-country data, regression coefficients
as in some of these studies did not show how the economy responded to population growth.
However, with the use of time series analysis, the data proved that there is a clear evidence that
population growth is associated with economic growth.
2.4 Conceptual framework
Conceptual framework was a hypothesized model that showed the relationship between the
variables in the form of charts or diagrams which helped in giving visual impression hence
enhancing understanding. It helped to give a quick glance of the proposed relationship that
existed and was put in the significance of the proposed relationship. The conceptual looked at the
impact of population growth on economic growth in Kenya.
32
INDEPENDENT VARIABLES
DEPENDENT VARIABLE
Birth rates
Death rates
Impacts of population growth on
economic growth
Migrations
33
CHAPTER THREE: RESEARCH METHODOLOGY
3.0; Introduction
In this section of the study the researcher presents a discussion on the research methodology that
will be adopted in investigating the impact of population growth on economic growth in Kenya.
Among the issues discussed include the research design, target population, sample size, data
collection technique, data validity and reliability and data analysis
3.1. Research Design.
Research design represents the master plan that specifies the methods and procedure for
analyzing data to achieve research objectives. The study used quantitative technique in response
to the scope of the research. It comprehends the structure within which research was conducted;
the preparation of which it was to facilitate research to be as efficient as possible, providing for
collection of relevant data with minimal expenditure of effort, time and money. The design in
this study will be the one to seek the relationship between population growth and economic
growth. The real GDP was used to measure economic growth in Kenyan shillings.
3.2 Model Specification
The study was anchored on the Simon-Steinmann Economic growth model. It lays a great
emphasis on population growth as a key contributor to the economic growth. Also, it implies that
for a nation to grow economically, its population must also grow. To establish whether
population change has any effect on the economic growth of Kenya, the study regressed GDP
Per capita against total population, population birthrate, population death rate and net migration
as a percentage of population. Just as in other empirical studies, the population of Kenya was
measured in terms of total number of people who were legally in the country at the specific time.
The regression was done while controlling for other macroeconomic factors affecting economic
34
growth, which included government expenditure in GDP, export share in GDP, import share in
GDP as well as inflation rate.
The model that was adopted during the study can be expressed as follows:
Y = β0 + β1X1 + β2X2+ β3X3 + ε
Where;
Y = Per capita GDP growth rate, 1960 - 2010.
X1 = Birth rate as a percentage of total population, in 1960 - 2010.
X2 = Death rate as a percentage total population from 1960-2010.
X3 = Migration as a percentage of total population from 1960-2010
β0, β1, β2 and β3, are constants
3.3. Data collection
This study made use of published data for the period ranging from 1960 to 2010. The main
sources of these data were: Kenya National Bureau of Statistics publications (KNBS) and World
Bamk (WB).
3.4 Data collection procedure
The research data was collected from secondary data extracted from Kenya National Bureau of
Statistic of 2017 report and world bank. The data on economic growth rate, birthrates, death rates
and migration per given years were obtained ranging from 1960-2010. The KNBS carried the
research based on the level of economic growth visa vis population birthrate, death rate and
migration which are the major variables of the study.
35
3.5 Data processing and analysis
The data analysis was done using regression analysis. A presentation for the findings was done
through the use of tables and graphs. Once the data was collected it was examined for accuracy,
consistency and completeness. The examined data was entered in numerical form to enable
statistical analysis. The data was regressed using Statistical Package for Social Sciences (SPSS)
version to analyze the relationship between economic growth and the chosen variables that is
birthrates, death rates and migration. The research employed quantitative methods of data
analysis. The regression analysis using Ordinary Least squares was conducted. Multiple
regression techniques were used to calculate the amount of variations of dependent variable
explained by independent variables through the co-efficient of determination (R2).
Hypothesis testing was done using relevant test statistics which was done with an aid of
computer package for analysis. The F-statistic tested the null hypothesis that the coefficients
values of subsequent variables are significant against the alternative hypothesis that the
coefficient values of a variable are not significant in the equation of the other variable. The null
hypothesis is rejected when F-statistic is greater than the F-value.
The relationship was assessed using multiple linear regression model consisting of independent
variables; birthrates, death rates and migration and dependent variable (economic growth)
measured by GDP in US Dollars.
To perform the various data analysis, the study used both descriptive and inferential statistics
where correlation and regression analysis were carried out for the data set of the period ranging
from 1960 to 2010.
36
CHAPTER FOUR: DATA PRESENTATION AND ANALYSIS
4.1 Introduction
This chapter presents analysis and findings of the study based on objectives of the following
themes: impact of population growth on economic growth in Kenya, determine the relationship
between the birthrates and economic growth in Kenya, evaluate the contribution of death rates on
economic growth in Kenya, examine the effects of migration on economic growth in Kenya. The
study examined the extent of the relationship between the dependent variable and independent
variables. From findings in the annex, the coefficient of determination squared (R2) shows the
proportional change of economic growth due to changes in birthrates, death rates and migration.
From the findings it shows that R2 is 86.3%. The above analysis means that 86.3% of all the
variations in economic growth are explained jointly by changes in birthrates, death rates and
migration.
According to annex 3 to aid in testing the significance of the variables of the study, calculated Fvalue is 97.498 while the F- critical value is 2.80 at 3:47 degrees of freedom. Based on these
results, the F-calculated is greater than F-critical and the null hypothesis should be rejected and
therefore work with the alternative hypothesis. Alternative hypothesis means that there is a
significant relationship between the independent variables (birthrates, death rates and migration)
and the dependent variable economic growth rate.
From the findings the following regression model was established;
Y=-1.296E+10+28517.987X1-13605.696X2-209761.648X3
From the findings of the regression analysis, it was found that holding the numbers of birthrates,
death rates and migration constant, economic growth would be -1.296E+10 (autonomous GDP).
37
The model further reveals that if birthrates changes by one unit on average, the GDP increases by
28517.987 units. For the death rates, a change of death rates by one unit leads to a decrease of
GDP by 13605.696 units. On the other hand, if migration changes by one unit, the GDP
decreases by 209761.648 units. This shows that the relationship between the dependent variable
and independent variables are both directly and inversely related. From the model, it is clear that
there is a direct relationship between the GDP and the birthrates while for the death rates and
migration the relationship between them and GDP is inverse.
4.2 The relationship between the birthrates and the GDP.
The 1st objective of the study was to determine the relationship between the birthrates and
economic growth (GDP). During the regression the following model was obtained;
Y=-1.296E+10+28517.987X1-13605.696X2-209761.648X3
the above model reveals that if birthrates changes by one unit on average, the GDP increases by
28517.987 units meaning that GDP is directly related to birthrates. This economic model
therefore encourages increase in the birthrates in order to attain and realize growth in the GDP.
In annex 4 below, the t-value of birthrates is 7.117 while the t-critical is 2.009 according tdistribution tables. Since t-value for the birthrates is greater than t-critical i.e. 7.117>2.009, we
therefore deduce that birthrate is not an important determinant of the GDP independently not
unless other variables are added as was seen in F-test. From the graph below, the number of
birthrates has been increasing steadily from 1960-1998 when there was a drop in the number of
births. The drop lasted for two years up to 2000 when a steady increase was witnessed again up
to the year 2000.
38
Fig 4.1; Number of births per year from 1960-2010
Birthrates
1600000
1400000
Birth Rates
1200000
1000000
800000
600000
400000
200000
2010
2008
2006
2004
2002
2000
1998
1996
1994
1992
1990
1988
1986
1984
1982
1980
1978
1976
1974
1972
1970
1968
1966
1964
1962
1960
0
Years
Birthrates
Source; researcher
4.3; Evaluate the contribution of death rates on GDP
Give that the objective of the study was to evaluate the contribution of death rates on GDP, the
analysis was done using regression method.
Regression was able to establish the following model;
Y=-1.296E+10+28517.987X1-13605.696X2-209761.648X3
From the above model, a change of the death rates by one unit on average decreases the GDP by
13605.696 units. There is inverse relationship between the death rates and the GDP. Therefore,
more deaths lead to decline in the level of the GDP.
39
In annex 4 below, the t-value of death rates is -0.867 while the t-critical is 2.009 according tdistribution tables, since t-value for the death rates is less than t-critical i.e. -0.867 < 2.009, we
therefore deduce that death rates is an important determinant of the GDP.
From the graph below the death rate has been gradually increasing from 1960 up to 1984 with an
average number of deaths of 170000 registered per year. From 1984 up to around 2001 there was
a rapid increase in the death rate more than any other period in Kenya’s history with an average
of 300000 deaths registered every year. This must have been as a result of HIV & AIDS
prevalence during that period since the disease was 1st witnessed in Kenya around 1983. From
the year 2002 up to 2010 again, there was a decline in the death rate though the average deaths
registered per year were still very high.
Fig 4.2;Number of deaths per year from 1960-2010
Death rates
450000
Number of deaths
400000
350000
300000
250000
200000
150000
100000
50000
Years
Death rates
Source; researcher
40
2010
2008
2006
2004
2002
2000
1998
1996
1994
1992
1990
1988
1986
1984
1982
1980
1978
1976
1974
1972
1970
1968
1966
1964
1962
1960
0
4.4: Effects of migration on economic growth
The 3rd objective of the study was to evaluate the effects of migration on GDP. The study used
net migration per give years and regressed it against the GDP. Regression model obtained to
evaluate the effect of migration on GDP was as follows;
Y=-1.296E+10+28517.987X1-13605.696X2-209761.648X3
From the model, when net migration changes by one unit on average, the GDP decreases by
209761.648 units. The model indicates an inverse relationship between the migration and the
GDP we should discourage emigration and encourage immigration of people into the country
which promotes an economic growth.
As indicated in the annex 4 below, the t-calculated value for the migration is -5.651 while tcritical is 2.009. since t-calculated for migration is less than t-critical i.e. -5.651< 2.009, we
therefore conclude that migration is an important determinant of the GDP and we should
discourage emigration and encourage immigration of people into the country.
As for migration as shown in the graph below, emigration rate was higher in the 1960s and early
1970s as compared to the immigration rate indicating the reason for the negative numbers in the
graph. The equilibrium between the immigrants and emigrants was almost attained in the 1980s.
The country however registered the highest number of immigrants from the year 1990 up to 1996
with an average of 20000 people registered per year during that period. In contrast, a rapid
decline was witnessed again from the year 1997 up to 2000 with an average of 20000 people
moving out to the foreign nations. There was a slight increase from the year 2001 up to 2006 but
again rapidly declined from the year 2007 up to 2010 with average 25000 emigrants registered
per year during that period.
41
Fig 4.3; Number of net migration per year
Migration
50000
40000
30000
20000
10000
-20000
-30000
-40000
-50000
Migration
42
2010
2008
2006
2004
2002
2000
1998
1996
1994
1992
1990
1988
1986
1984
1982
1980
1978
1976
1974
1972
1970
1968
1966
1964
1962
-10000
1960
0
CHAPTER FIVE: SUMMARY, CONCLUSIONS AND RECOMMENDATIONS.
5.1: Introduction
This chapter present discussion on summary of the study, conclusion and recommendations on
the on impact of population growth on economic growth in Kenya. On addition this chapter
outlines contribution to knowledge and areas for further research.
5.2 : Summary
The study intended to find the impact of population growth on economic in Kenya. The analysis
was based on objectives of the study as discussed below; The 1st objective was to determine the
relationship between birthrates and economic growth in Kenya. From the analysis using the
regression model it was found that when birth rates change by one unit on average, the GDP
increases by 28517.987 units as shown in the model below
Y=-1.296E+10+28517.987X1-13605.696X2-209761.648X3
This has a potential of increasing the GDP in the country as higher birthrates is directly related
to the higher GDP resulting to the economic growth. The other objective was to evaluate the
contribution of the death rates on economic growth in Kenya. Analysis was done to show
relationship between the GDP and death rates and from the regression model above it was found
that there is an inverse relationship between the GDP and the death rates as higher death rates
leads to a decline in the GDP growth. From the model when death rates change by one unit on
average, the GDP decreases by 13605.696 units. This implied that high levels of death rates
within a country leads to a steady decline in the GDP growth. With decreased GDP the economic
growth rate also decreases in general.
43
The last objective of the study was to examine the effects of migration on economic growth in
Kenya. Migration is strongly related to the economic growth as was shown by the regression
model above. From the model when migration changes by one unit on average the GDP
decreases by 209671.648 units. GDP and migration are inversely related as higher net migration
leads to a decline in levels of GDP attained in the country. This implies, with increased net
migration of people the GDP growth rate is likely to be registered because the people within a
country at a particular time will be consuming goods within that country and participate in nation
building activities like payment taxes to the government. Therefore, the higher GDP growth rate
can be achieved by restricting net migration of resulting to brain drain.
With the above objectives the study found that previous reviews only focussed on how
population policies affect the GDP of a given country but not suggesting how the components of
population e.g. birthrates death rates and migration affect the GDP.
5.3: Conclusion
The findings of the study show that population growth rate plays a great role in the economic
growth rate in Kenya as shown by adjusted R2 of 85.3% meaning that 85.3% of variations in the
GDP are explained jointly by the birthrates, death rates and migration. The study also concludes
that higher birthrates should be encouraged as this increases the level of economic growth in
country. With ease access to health services and provision of reliable maternity services the
birthrates increase thereby leading to increase in the GDP.
The study also conclude death rates leads to a decline in the GDP as shown in the regression
model where a change of death rates by one unit leads to decrease of GDP by 13605.696 units.
The GDP and the death rates are therefore inversely related as increase in death rates leads to a
44
decrease in the GDP. With increased levels of the death rate of a given country the GDP will
steadily decline thereby resulting to low levels of economic growth rates.
On the migrations the study found the GDP is inversely related with the migration as shown in
the regression model. In the model, if migration changes by one unit on average the GDP
declines by 209761.648 units. The findings show that in order to achieve a GDP growth, the
emigration of people should be discouraged as it leads to a steady decline in the rates of GDP
growth hence decline in the economic growth in country.
5.4. Policy Recommendations
With the results indicating a direct relationship between the population growth and economic
growth in Kenya, then a carefully planned population growth strategy coupled with institutional
and policy changes could be beneficial to this country. A well-managed population expansion
will ensure that both the population growth and the economic growth are complementing each
other without concerns that population expansion will lead the country into famines and lack of
other socio-economic facilities since it’s the inadequate government policies, rather than
population growth which are responsible for the woes including, famines that besiege most
developing nations. Based on our analysis and research findings, we recommend the following
policy guidelines:
➢ It is recommended that the average population growth rate in Kenya should be
maintained since it is found to impact positively on economic growth in Kenya within
the period of study.
➢ The economy of Kenya should be diversified to enhance productivity of labor and
economic growth as population increases.
45
➢ Kenyans should be encouraged to save since an increase in savings results to increase in
investment leading to employment creation for the growing population. Savings will also
be used to invest in more research and new techniques. Each of these techniques being a
less than perfect substitute requiring more labor or resource of a different, more laborintensive type and therefore added more value-added services to the production. This
continues to add to the total output at a higher rate than population growth, raising per
capital out as a result.
➢ Government should make concerted effort to come up with the favorable migration
policies to reduce the emigration of potentially active work force and professionals into
other countries as this reduces the GDP
➢ Government through parliament should pass a legislation for a compulsory universal
healthcare for all the citizens to reduce the incidences of the death rates.
➢ A better political environment would also encourage private investment since its
contribution to economic growth cannot be under estimated.
➢ . Policy- makers should come up with policies that ensures that full utilization of
resources are effective to sustain the growing population.
5.5; Contribution to knowledge
The finding of the study give support to the population-driven economic growth hypothesis that
states that the population growth in a country promotes its economic growth development.
5.6: Areas for Further Research
The study concentrated much on only four aspects of population growth. There are so many
other demographic factors that can be seen to influence the country’s economic condition. Some
46
of these factors include the various age brackets, rural population, the working population,
population density and population distribution. The study, therefore, leaves the gap where further
researchers can determine the effect of these factors on the economy of the country.
47
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Lesthaeghe, R. (2005). Reproduction and Social Organization in Sub-Saharan Africa. Berkeley;
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United States of America, Bureau of the Census (2001). The International Data Base (IDB
49
Table of data collected
YEAR GDP(US$)
Birthrates Deathrates Migration
1960
791265458
415809
163729
0
1961
792959472
428105
163884
-334
1962
868111400
440940
164813
-89
1963
926589348
453438
165696
-2583
1964
998759333
467367
166522
-3496
1965
997919319
482838
167282
-42
1966
1165000000
498000
168946
-4223
1967
1233000000
514832
169579
-4163
1968
1353000000
532463
171186
4200
1969
1458000000
550993
172796
4238
1970
1603000000
570501
173288
-3907
1971
1778000000
592201
174862
-4196
1972
2107000000
613825
176414
-4108
1973
2502000000
635263
177923
-4009
1974
2973000000
657678
179366
-3899
1975
3259000000
681074
180720
-3583
1976
3475000000
704034
181957
-2799
1977
4494000000
727867
183053
-1598
1978
5304000000
752641
184012
-1357
1979
6234000000
776877
186387
-939
1980
7265000000
803688
187093
-585
1981
6854000000
828182
189298
-507
1982
6432000000
870947
191397
-351
1983
5979000000
879139
195161
364
1984
6191000000
901436
198846
568
1985
6135000000
923607
204372
761
1986
7239000000
943530
209899
855
1987
7239000000
958817
217528
924
50
1988
8355000000
971092
225275
1049
1989
8283000000
982273
233120
1109
1990
8572000000
992266
243386
1005
1991
8151000000
1003453
256303
7253
1992
8209000000
1021025
269610
17474
1993
5752000000
1040466
285870
23178
1994
7148000000
1064594
299997
39822
1995
9046000000
1093858
317218
44314
1996
12046000000 1125909
334958
42221
1997
13116000000 1161059
353240
26058
1998
14094000000 1193769
366168
20838
1999
12896000000 1124015
379444
306
2000
12705000000 1223423
389985
-4277
2001
12986000000 1279930
397554
-2908
2002
13148000000 1301989
398568
-1328
2003
14905000000 1327690
392504
341
2004
16095000000 1353892
385824
4559
2005
18738000000 1377044
374902
5029
2006
25826000000 1396862
359404
4816
2007
31958000000 1416795
342773
1523
2008
35895000000 1428917
328846
-38408
2009
37022000000 1440491
313850
-38627
2010
40000000000 1451390
301856
-37866
51
Annex 1; Variables Entered/Removed
Variables
Variables
Model Entered
Removed
Method
1
MIGRATION,
BIRTHRATE
S,
.
DEATHRAT
ESb
Enter
a. Dependent Variable: GROSS DOMESTIC
PRODUCT
b. All requested variables entered.
Annex 2: Model Summary
Change Statistics
Model R
1
R
Adjusted Std. Error of the R Square
Square R Square Estimate
Change
.928a .862
.853
3681626061.988
.862
60
F Change
df1
Sig. F
Chang
df2 e
97.498
3
47
a. Predictors: (Constant), MIGRATION, BIRTHRATES, DEATHRATES
Annex 3: ANOVA
Sum of
Squares
Model
1
df
Regression 396456921412
4923300000.0 3
00
Residual
637055411634
742400000.00 47
0
Total
46016246257
59665500000. 50
000
Mean Square F
Sig.
132152307137
4974500000.0 97.498
00
.000b
135543704603
13668000.000
a. Dependent Variable: GROSS DOMESTIC PRODUCT
52
.000
b. Predictors: (Constant), MIGRATION, BIRTHRATES, DEATHRATES
53
Annex 4: Coefficients
Model
1
Unstandardized
Coefficients
Standardize
d
Coefficient
s
B
Beta
Std. Error
(Const 1645819233.
ant)
1296141838
167
0.396
95.0% Confidence
Interval for B
t
Sig.
Lower
Bound
Upper
Bound
-7.875 .000
162723796 965045715
10.032
0.759
BIRTH
RATE 28517.987 4006.769
S
.957
7.117
.000
20457.407 36578.566
DEAT
HRAT -13605.696 15695.193
ES
-.118
-.867
.390
-45180.352 17968.960
MIGR
ATIO -209761.648 37119.045
N
-.337
-5.651 .000
a. Dependent Variable: GROSS DOMESTIC PRODUCT
54
284435.535 135087.760
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