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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 vi 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 2 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 REFERENCE Aguirre, M. S. (2007) Population Resources and Environment: A Survey of the Debate‘‘, The Catholic Family and Human Right Institute.TheCatholic University of America. Caldwell J.C (2002). The Theory of Fertility Decline. Academic Press, New York. Caldwell, John C. I. O. Oruboloye, and Pat Caldwell (2006). Fertility Decline in Africa: A new type of transition? Population and Development Review 9new York) 1vol.8, No.2, pp. 211-242. Central Bank of Nigeria Statistical Bulletin 2008. Coale, A. J and Hoover, E. A (2007). Population Growth and Economic Development in Lowincome Countries. Princeton, New Jersey; Princeton University Press. Damoder, N. Gujarati (2003) ―Basic Economics ‘‘. Tata McGraw-Hill Book Company Limited, New York. Easterlin, R. A. and E. M. Crimmins (2001). The Fertility Revolution: A Supply-Demand Analysis. Chicogo: University of Nigeria Chicago Press. Federal Ministry of Healh (1998). National Policy on population for Development, Unity, Progress and Self-reliance. Federal Ministry of Health, Lagos, Nigeria. Furedi, F. (2004) Population and Development: A Critical Introduction ‘‘In Aguirre, M.S. ed population, Resources and Development. Ibeahim, Mantu (2001). Implications of population Growth for the Nigeria Economy and Environmental. Olive de L‘Afrique Consult Abuja 48 Lesthaeghe, R. (2005). Reproduction and Social Organization in Sub-Saharan Africa. Berkeley; University of California Press, Berkeley. Macunovich, J. Diane (2000). Relative Cohort Size: Source of a unifying theory of global fertility transition? Population and Development Review, vol.26, No.20 pp.235-261. Michael, P. Todaro, Stephen C. Smith (2003). Economic Development, Pearson Education (Singapore) etc. Ltd, India Branch. Mohammad Jalal Abbasi – Shavazi and G. W. Jones (2001). Socio-Economic and Demographic Setting of Muslim populations. National population Commission (2000). Nigeria Demographic Health survey 1999. Calverton, Maryland: National population Commission and ORC/Macro. Ogujiuba, Kanayo (2005). Challenges of population Dynamics in Nigeria: Implications of Household‘s Portfolio Choices. Department of Economics, University of Nigeria. Oladosu, Muyiwa (2001). Prospects for Fertility Decline in Nigeria: Comparative Analysis of the 1990 and 1999 NDHS data. Taylor and Francis, (2008). Consequences of Rapid Population Growth in Developing Countries. New York Inc. United Nations (2006). World population Prospects. The 1998 Revision Comprehensive Tables. Vol.1, New York. 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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