BBSE Research Projects (2021)

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    The effect of foreign direct investment on the level of carbon emissions in Kenya
    (Strathmore University, 2021) Marcellus, Ehete Kenneth
    Foreign direct investment (FDI) can be thought of as either a blessing or a curse to the economies of countries. The study was investigating the impact FDI has on the level of carbon emissions Through FDI, growth of the economy is witnessed. However, it also serves as an avenue for dumping with hazardous effects to the environment. This study examines the effect that foreign direct investment has on the level of carbon emissions in Kenya. The period of study is from 1960-2016. A long run relationship was realized between the explanatory variables and carbon emissions. Owing to this fact a Vector error correction model was most relevant for the study especially in estimating the short run effect. From the results obtained, it is evident that foreign direct investment has a decreasing effect on the level of carbon emissions in both the short and long run. Meaning that with an increase in FDI, a significant reduction in carbon emissions is noted in Kenya. A recommendation made is that the government and policy makers actively and effectively monitor and evaluate adherence to the laid out policies by both foreign investors and foreign related investments. One constraint while carrying out the project was the lack of an abundant dataset. For further research, being able to obtain the sectoral breakdown of how FDI is distributed and carrying out a research based on a sectoral view will be able to give more insight into the topic.
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    Coronary Heart disease prediction in the USA and factors that favor its occurrence
    (Strathmore University, 2021) Gachanja, Jeremy Kibiru
    Coronary Heart Disease (CHD) is the leading cause of deaths in adults in Europe ~md North America (WHO, 2017) . Early detection and treatment of this disease is thus a matter of life and death (Gonsalves, Thabtah, Mohammad, & Singh, 2019). This project has compared the predictive power of five machine learning algorithms namely: Support Vector Machine, Naive Bayes, Logistic Regression, Decision Trees and Neural Networks, in predicting this disease. The objective of this study was to determine which of the five algorithms was best suited for CHD prediction and what level of the CHD risk factors favored the occmrence of CHD. This study had fourteen CHD risk factors that is gender, age, smoking habit, number of cigarettes smoked, use of blood pressure medication, prevalent stroke, prevalent hypetiension, diabetes, total cholesterol, diastolic and systolic blood pressure, BMI, heart rate, and education. However, this study found that only age, systolic and diastolic blood pressure, prevalent hypertension, blood pressure medication and diabetes had a significant correlation with CHD occurrence. This study used these seven CHD risk factors to model CHD occurrence in the five algorithms. This study found that the logistic regression was best suited for predicting CHD, followed by Naive Bayes then Decision Tree and lastly SVM and Neural Networks. This work found that CHD positive individuals had high cholesterol (235mm on average), high blood sugar (a maximum of 394mm), had a smoking habit (10.82 cigarettes per day on average), were obese (overweight BMI of 26.63 on average) and had high blood pressure (a maximwn of 295/140 Mm Hg and 143/86 Mm Hg on average
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    Modelling the optimal growth- maximizing public debt threshold: A case for Kenya
    (Strathmore University, 2021) Chakairu, Isabel Wamuyu-
    This paper attempts to estimate the optimal growth -maximizing public debt threshold for Kenya by assessing the relationship between public debt and economic growth. The analysis determines the tipping point beyond which Kenya's economic growth would be adversely affected. The paper thus contributes to the debate in Kenya on whether the move by government to take up huge bilateral and multilateral debt will in the long run be detrimental to the economy. A bilateral quadratic equation is used to fit the non - linear relationship. The results confirm existence of a concave relationship between public debt and economic growth which is estimated to be optimal at around 45 to 50 percent for Kenya. The policy implication for the analysis· is the need to ensure that public debt management policies are in line with the growth - maximizing public debt threshold. This will ensure sustained economic growth and employment rates, which are key tenets for sustainable economic development.
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    ICT development and economic growth: Are southeast African countries doing enough to leverage on ICT?
    (Strathmore University, 2021) Amusudzu, Luvindi Mwingisi
    ICT is fast growing across continents and has brought about aspects of economic growth within countries, particularly developed countries. Over the years, productivity has noticeably increased with businesses and governments having easy access to global markets, hence improved trade openness. In this study, we analyze the state of ICT in Southeast African countries to understand whether ICT has been underutilized or to whether they are leveraging the use of it. From literature, Solow (1956) and Swan (1956) have argued that absence of technology innovation leads to economic stagnation that leads to high unemployment. In this study, we analyze ICT and its impact on unemployment as well as human capital in Southeast Africa. Also, the study analyzes consumption expenditure, trade and inflation and their relationship with ICT while alluding that they could be potential growth enhancing factors ofiCT. The study proposes to use a two-step system generalized method of moments (GMM) estimation technique while drawing its theoretical underpinnings from the neo-classical growth model.
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    The effect of technological innovation on economic growth: Empirical evidence from Kenya
    (Strathmore University, 2021) Mohammed, Leila Haroon
    Kenya's recent classification as a Lower- middle-income country (LMIC) is proof that the economy of Kenya is growing as per the Vis on 2030 Plan set in 2008. As technological innovation development is a known factor for increasing the growth of a nation's economy, Kenya's objective to transition into a knowledge-based economy requires a proper understanding of the relationship between technological innovation, that produces technological knowledge, and economic growth. This study puts technological innovation into perspective and aims to empirically examine its relationship to economic growth. It employs the use of Patent registered, Number of trademarks registered in Kenya, and Scientific and Teclmical Journal articles in Kenya as measures of technological innovation as well as Labour productivity Growth rate as a proxy for economic growth. It establishes whether there exists a long-run relationship between technological innovation and economic growth from 1981 to 2018 with data sourced from The World Bank database. This study also seeks to examine whether there exists bidirectional causality between technological innovation and economic growth. The Autoregressive distributed Lag model and pairwise Granger causality test technique are used for estimation. There is a short run relationship between total number of patent applications and Labour productivity growth rate although the impact is quite small. There is no presence of a significant long run relationship between technological innovation and economic growth. The study also concludes that, there exists no bidirectional granger causality between technological innovation and economic growth.