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Effect of Financial Accountability on Financial Sustainability of Microfinance Institutions in Kenya
Get PDFThe study seeks to identify how financial accountability helps the MFIs in terms of financial sustainability in Kenya. As per 2002, the number of MFIs have increased to 14 form 10 while the number of accounts opened for deposit purposes are twenty thousand. This has been indicated to be a decrease, (GOK, 2020), due to the high cost of living. With this reduction, there has been an increase in the loan default according to the CRB. Microfinance has exhibited success as a bridge to poverty reduction, but the issue at hand is to make microfinance institutions sustainable and have fewer defaults from borrowers. By increasing the number of individuals reached, and the number of financial products, it can be made available not just to the moderate poor at whom it has traditionally been targeted, but also to the extremely poor and the vulnerable non-poor. Therefore, the main objective of this research study will be to find out the effect of financial accountability on financial sustainability of Microfinance Institution in Kenya. The specific objectives were to determine how financial control, financial monitoring, financial planning and transparency affect financial sustainability. On the theoretical review the study will be guided by three theories: principal-agent theory (agency theory), Resource mobilization theory and social strain theory. Descriptive research design will be used in the study. The target population includes managerial staffs which is a total of 145 head office heads, middle level officers and lower-level officers in the microfinance institution in Kenya. Stratified random sampling will be used to arrive at target group while simple random sampling will be done to get the sample size. The sample size is 73.1% of the target population which is 106 respondents. Data will be collected using Questionnaires. The study will use the quantitative and qualitative data analysis methods
Relationship Between Current Account Deficit And Economic Growth In Kenya
Get PDFCurrent account balance is a salient macroeconomic indicator of an economy’s
performance. Current account deficits are majorly as a result of trade balance
deficits caused by low export of commodities and services compared to
importation. This study sought to establish the connection between the current
account deficit and economic growth in Kenya. Specifically, this study sought to
investigate the nexus between the merchandise trade deficit, services account
surplus, primary income deficit, secondary income surplus and economic growth in
Kenya. This study employed a descriptive research approach. Data on study
variables was collected for the period between 1999 and 2021. From the
International Monetary Fund database's, pertinent information was retrieved.
Additional secondary information was gathered from the internet, the Central Bank
data base and the Economic Surveys. The models employed included; the Johansen
cointegration test, and the Vector Autoregressive model. The study applied the use
of STATA statistical program. It was established that merchandise trade deficit has
a negative and significant relationship with economic growth in Kenya. The study
found that services account surplus has a negative and significant relationship with
economic growth in Kenya. It was established that secondary income surplus has a
negative and significant relationship with economic growth in Kenya. Primary
income deficit had a negative, but non-significant relationship with economic
growth in Kenya. The study concludes that current account deficit has negative but
significant relationship with economic growth in Kenya. The study recommends
that the government of Kenya should prioritize the promotion of exports of goods
to reduce merchandise trade deficit. The study recommends that the government
should reduce the reliance on services exports such as travel by promoting other
sectors, such as manufacturing or agriculture. Lastly, the government should also
promote export-oriented industries that can generate foreign exchange and reduce
reliance on secondary income source
Effect of Supply Chain Management Practices on Organizational Performance of Parastatals in Kenya.
No full textThe aim of this study was to determine the effect of supply chain management practices on the performance of Kenya’s state corporations. The study adopted a descriptive research design. A total of 142 parastatals were targeted from which 15 of them were selected to participate in the study. Purposive sampling was used to select two senior managers from each of the 15 parastatals. These respondents were selected from the finance and procurement departments. Questionnaires were used to collect primary data from the state corporations. Both descriptive and inferential statistics were used in the study. Inferential statistics conducted were regression analyses. Results indicated that outsourcing practices (p=0.205>0.05) have a negative but insignificant effect on organizational performance. On the other hand, inventory management practices(p=0.006<0.05), lean practices (p=0.006<0.05), and strategic supplier relationship management practices(p=0.001<0.05) all have a positive and significant effect on the performance of state corporations
Let’s harvest water during rainy season
No full textWe are a few days to the onset of the much-awaited long rains. The weatherman has issued a warning that the rains may be below average. This is disheartening news after a period of prolonged drought, but the encouraging bit, there will be some rain.
The rains may be delayed, may fall over a short period, and there might be some flash floods in some regions, but one thing is sure
Impact Investing and Sustainable Livelihoods of Dairy Farmers at Githunguri Sub County, Kiambu County in Kenya
No full textThe study sought to establish the effect of impact investing on sustainable livelihoods of dairy farmers operating in Kenya. The study focused on impact investing practices comprising of microfinance products, contract farming and environmental conservation practices. A descriptive research design was adopted in the study. The target population comprised of 22,644 farmers distributed in the 5 Wards of Githunguri Sub County in Kiambu County, Kenya. Yamane Sampling formula was utilized in deriving a sample of 398 respondents where stratified random sampling technique was adopted to randomly select the sample in the 5 wards. Quantitative data was utilized in the study and was collected through a structured questionnaire. Both descriptive and inferential statistics were employed in analyzing the gathered data. SPSS software was utilized in generating the statistics. The analysis results established that microfinance products and contract farming bear positive and significant effects on sustainable livelihoods of dairy farmers operating in Githunguri Sub County, Kiambu County. Environmental conservation practices were found to have a positive but insignificant effect on sustainable livelihoods of dairy farmers
Effect Of Financial Soundness Indicators On The Performance Of Listed Insurance Companies In Kenya.
Get PDFThis study investigates the impact of financial soundness indicators on the performance of listed
insurance companies in Kenya. Drawing from Shareholder’s Theory, Capital Buffer Theory, and
Portfolio Theory, the study aims to evaluate the effects of capital adequacy, managerial
effectiveness, earning potential, and liquidity on the performance of insurance firms. Utilizing a
descriptive research design, dynamic panel data from 2008 to 2022 is employed for analysis. The
target audience comprises six insurance firms as of December 2022, all included in the study
through a census approach due to the small sample size. The findings reveal significant insights
into the relationship between financial soundness indicators and the performance of insurance
firms. Firstly, capital adequacy emerges as crucial for ensuring the financial stability of insurance
firms, with ample capital facilitating smoother operations amidst the sector's inherent volatility.
This aligns with previous research indicating a positive correlation between capital levels and
financial stability. However, managerial effectiveness is found to have a counterproductive effect,
potentially due to increased operational costs in the short term. This finding contrasts with studies
in the banking sector, suggesting differences in business dynamics between insurance and banking.
Moreover, earning potential is identified as a key determinant of performance, emphasizing the
importance of sustainable returns and earning quality for insurance firms. The study underscores
the need for firms to continually assess and adapt to environmental risks to maintain financial
standing. Interestingly, liquidity is found to have a negative impact on performance, as high liquid
asset holdings limit opportunities for profitable investments, unlike findings in the banking sector.
In conclusion, this research highlights the complex interplay between financial soundness
indicators and insurance firm performance in Kenya. It emphasizes the significance of capital
adequacy and earning potential while acknowledging the nuanced effects of managerial
effectiveness and liquidity. Based on these findings, recommendations are made for insurance
firms to prioritize capital management, sustainable earnings, and prudent liquidity strategies to
enhance overall performance and long-term sustainability in the dynamic insurance landscape of Kenya
Effect Of Sustainability Finance Practices On Organizational Performance Of Commercial Banks In Kenya
Get PDFThe study focused on the adoption and implementation of sustainability finance practices by commercial banks in Kenya and their impact on organizational performance. It highlights the challenges posed by unsustainable business models and the need for coordinated sustainability initiatives within the banking sector. The research aims to examine the effects of environmental, social, and governance sustainability on banks' performance, based on theories such as agency, stakeholders', and legitimacy theories. The study used a descriptive research design and targeted all 39 licensed commercial banks in Kenya. A sample of 117 senior finance managers were selected using a simple random sampling technique, and data was collected through a structured questionnaire. The findings suggest that banks in Kenya are actively engaged in sustainability practices, including the production of sustainability reports, environmental policy statements, staff training, and diverse board compositions. These practices have the potential to positively influence organizational performance by fostering responsible and ethical operations. However, the study acknowledges the need for more representative samples and continued efforts to address demographic imbalances in future research
A Time Series Model For Forecasting Lake Expansion: Case Study Of Lake Baringo
Get PDFA flood is a natural disaster that refers to the temporal overflow of water on top of land that
was previously not inhabited by water. It can be caused by too much precipitation or even
outbursts of water reservoirs due to other reasons. Severe Floods have occurred in the Rift
Valley lakes since 2011 due to lake expansion. Floods in the Lake Baringo area have occurred
due to overflows of the lake and is a dangerous disaster leading to many pros rather than cons.
It is due to the major problems experienced that the need for the use of Machine Learning, GIS,
and Remote Sensing arose to help in monitoring, and creation of a forecast model to help create
awareness of the area that is likely to be affected by floods in the future years. The research
was guided by three objectives: Determining factors leading to the expansion of Lake Baringo,
mapping spatial-temporal change in the Lake Baringo region to help compare the changes,
comparing the time-series algorithms (LSTM and GRU) efficiency in the training of the dataset
and lastly developing a time-series model for forecasting the area growth of Lake Baringo.
Earlier researchers had used GIS and RS for the monitoring of similar cases but the element of
prediction was not well looked into. Machine Learning methods have also been used to create
prediction models but in the case of lake area expansion limited researchers had explored,
hence the identified gaps arose. The research design used was longitudinal and it comprised
two sets of data mainly satellite images and previously recorded data. Images were used for
classification to map the changes over time and to visualize the lake's growth, the other form
of dataset was used for analysis and creation of the model. GRU outperformed the LSTM
algorithm ass per metrics, it was found that Lake Baringo had expanded by 50% from the year
2011 mainly due to increased rainfall and reduced evaporation increasing the rate of
sedimentation which led to the rising of the lake level. The study was limited by the available
data and time used in the image analysis. The objectives were achieved and, in the future, better
models could be developed for numerous lakes in Kenya and not only Lake Baringo
Modelling credit risk using system dynamics: The case of licensed credit reference bureaus in Kenya
No full textCredit reference bureaus (CRBs) have been operational in Kenya for many years owing to the large number of borrowers who fail to repay their loans. However, regulating how credit risk will be quantified by these CRBs is often based on standards and assumptions that are not practical to the real-world scenario. This study models credit risk to discover more effective and practical measures which relate to the borrowers and their operating environment. Data was collected from annual default reports from the Central bank of Kenya, CRBs and major financial institutions over a period of three years (2018, 2019, and 2020). The study also used focus group discussions to establish the key default factors and their baseline values. A sample of 29 participants was drawn from the population of CRB staff members who undertake the core functions of credit risk determination. Using the system dynamic modeling and simulation approach, the study identified faithful representations of default risk measurements. First, descriptive analysis was conducted using tabled summaries and bar charts and results identified customer income, issued loans and collateral amount as the most influential factors for credit risk. Explorative analysis applied causal loop diagrams (CLDs). Simulation analysis was then conducted after generating stock-and-flow diagrams and three important variables were identified, i.e., loan repayment, performing loans, and credit risk. The information gained from this study will benefit the government, the Central bank of Kenya (CBK), research scholars and other major financial institutions around the country