Browsing by Author "Njuguna, Angelica"

Now showing 1 - 4 of 4
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    The Effect of The Size of the Informal Sector on Economic Growth in Kenya (1974 to 2016)
    (International Journal of Social Science and Economic Research, 2019) Opondo, Mary Awuor; Etyang', Martin N.; Okeri, Susan; Njuguna, Angelica
    The Kenyan economy is dual and predominantly informal. The size of the sector in the country has grown over time. The sector employed 19 percent of the total workforce in 1974 which increased to 84 percent in 2016. The country targets economic growth averaging 10 percent per annum, and a reduction in poverty rates to 28 percent of the total population by the year 2030. Efforts to develop the sector for economic growth, employment creation and poverty reduction can be traced to the period 1986, under the Sessional Paper No.2 of 1986 on Economic Management for Renewed Growth. The growth of the informal sector in the country has led to a marked increase in employment numbers, but not much is known about the effect on the other two objectives, which are economic growth and poverty reduction. Reports on the contribution of the sector to economic growth are largely conflicting with limited econometric studies. The study analyzed the relationship between the size of the informal sector and economic growth in Kenya. A growth accounting exercise was conducted using the standard Cobb-Douglas production function. From the study findings, the informal sector is the lowest contributor to output growth in the country. Given the size of the sector the study concludes that there is a need to target increased productivity in the informal sector for increased economic growth.
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    Enhancing Growth and Productivity Through Mobile Money Financial Technology Services: The Case of M-Pesa in Kenya
    (Canadian Center of Science and Education, 2023-11-20) Wachira, Gladys; Njuguna, Angelica
    Kenya’s financial industry has been revolutionized and progressing to digital transformation since M-pesa, a mobile money financial technology service, was introduced in 2007. An M-pesa account allows subscribers to send and receive payments as well as store money. As the digital system grew rapidly, a high percentage of Kenyan households gained access to this service, subsequently helping the unbanked and underbanked populations toward broader financial inclusion. As an efficient and highly adaptable payments system communicating across all markets in the economy, M-pesa has contributed to financial deepening, hence promoting economic development. This study analyzed the effects of mobile money financial technology services on Kenya’s output growth and productivity. The findings suggest evidence of a structural change in the growth of output and total factor productivity when M-Pesa was introduced. Mobile Money was established to have had a significant positive effect on enhancing output productivity and output growth.
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    Revisiting the Dynamics of Stock Market Returns Volatility of Listed Companies under the NSE 20 Share Index in Kenya
    (Eurasian Journal of Economics and Statistics, 2024-10) Ngigi, Daniel; Njuguna, Angelica
    This study explored the behavior of stock market returns volatility in the Nairobi Securities Exchange (NSE) for listed companies under the NSE 20 share index in Kenya. The study analyzed stock returns using 2,999 observations from 3 January 2011 to 30 December 2020 and estimated a generalized autoregressive conditional heteroskedasticity, GARCH (1,1) and an exponential generalized autoregressive conditional heteroskedasticity, EGARCH (1,1) models. The study found that the stock returns volatility of companies listed under the NSE 20 share index exhibited both volatility clustering and persistence behavior. However, there was no evidence of the leverage effect on future volatility in returns.
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    Total debt servicing and macroeconomic performance in Kenya
    (2015-04) Otieno, Joshua Magero; Njuguna, Angelica; Njaramba, Jeniffer
    Kenya seeks to meet the Millennium Development Goals, under the guidance of The Kenya Vision 2030. The leading challenge to this course remains the soaring debt servicing obligations, capturing a significant portion of the national budget. Kenya has been borrowing externally at higher rates and continually expanding the debt ceiling. The government will therefore in future spend a significant portion of its revenue repaying the debts at the cost of important local investment. The government is therefore limited to fully fund critical sectors of the economy that will spur sustainable growth and increased investment opportunities; key to widening the tax base. This has an overall implication on the country‟s revenue, income, employment and poverty level. This study aimed at determining the long-run relationship between total debt service and selected macroeconomic variables and to analyze the dynamic response of the variables following innovations in total debt service. Long run equations expressing the relationship between total debt service and real Gross Domestic Product, Real effective Exchange Rate and private investment were estimated. The results showed evidence of crowding out effect but no existence of debt overhang. Kenya was also found to have weak policy institutions thus remained vulnerable to adverse global exogenous shocks. In analyzing the dynamic impact of innovations in debt servicing on selected macroeconomic variables, a Vector Autoregressive (VAR) model was estimated with subsequent derivation of the Impulse Response Functions (IRF) and Variance Decompositions that explained the dynamics of the model. Based on the results, the impact of an unexpected shock in total debt service in the economy lasts for more than ten years to fully decay. The study tested time series behaviours like presence of unit root and serial correlation in the data to guard against spurious results. A string of diagnostic tests were also undertaken to establish the predictive power of the models. The Akaike Information Criterion (AIC) was used to determine the optimal lag length of the variables included in the VAR model.