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This study investigated the impact of healthcare interventions by agricultural cooperatives on women's recovery during the post-COVID-19 period in Kajiado County, Kenya. It explored how agricultural cooperatives address women's recovery in the post-COVID-19 period in Kajiado County. It examined support initiatives for women's recovery, internal healthcare mechanisms targeting women, and cooperative-led interventions in post-COVID-19 recovery. Supported by Social Capital Theory and Empowerment theory, the study focused on Kajiado County. Kajiado County was selected for its cultural diversity and economic activities. Utilizing a mixed-methods research design, the study included a sample size of 373 respondents, members of agricultural cooperatives. The qualitative phase involved interviews and focus groups, while the quantitative data was collected using structured questionnaires. This study employed a combination of stratified random sampling and purposive sampling. Findings were presented through tables, aiming to inform government regulators in policy formulation. The study concluded that women have largely positive perceptions of the healthcare interventions offered by agricultural cooperatives. The findings also suggested a strong positive correlation between women's experiences with healthcare initiatives and their recovery from the COVID-19 pandemic. The study further concluded that logistical and cultural barriers remain significant obstacles to women's access to healthcare services provided by agricultural cooperatives. Recommending that agricultural cooperatives must develop and implement robust communication strategies to bridge the gap between awareness and actual engagement in healthcare programs for women. The study encourages policymakers to work alongside cooperatives to broaden these programs, create accessible healthcare models that consider rural challenges, and overcome existing logistical and cultural obstacles. By building such collaborative frameworks, these efforts can enhance women’s resilience, support sustainable recovery, and contribute to enduring improvements in community health and economic resilience in rural areas.

Policymakers and scholars acknowledge the significance of small and medium enterprises in stirring the economic growth and development in developing and developed economies. In spite of the generally fast pace by which access to financial services for small and medium enterprises is being established, significant segments of the small and medium enterprises sector do not yet benefit from the expansion. This study, therefore, investigated the effect of relationship lending on access to financial services by small and medium enterprises in Kenya. The study was based on credit rationing theory and information asymmetry theory. The target population comprised 4,253 small and medium enterprises in Kenya. A sample size of 366 SMEs was used by the study. The study adopted a multistage sampling technique to obtain the SME respondents. Primary data was utilized and was acquired through semi-structured questionnaires. Data were analyzed using descriptive and inferential statistics utilizing Heckman two-stage regression model. The study findings showed that relationship lending had a positive and significant effect on access to financial services among SMEs in Kenya. The study concluded that relationship lending plays a critical role in access to financial services by SMEs in Kenya. The study recommends that SMEs owners should strive to meet the terms and conditions provided by lending institutions in their various financing practices while management of the lending institutions should adopt financing practices favorable to SMEs to increase their access to financial services.

This study sought to model the stock market return volatility at the Nairobi Securities Exchange (NSE) in the presence of structural breaks. Using daily NSE 20 share index for the period 04/01/2010  to  29/12/2017,  the market return volatility was modeled using different GARCH type models and taking into account four endogenously identified structural breaks. The market exhibited a non-normal distribution that was leptokurtic and negatively skewed and also showed evidence for ARCH effects, volatility clustering, and volatility persistence. We found that by considering structural breaks, volatility persistence was reduced, while leverage effects were found to lead to explosive volatility. In addition, investors were not rewarded for taking up additional risk since the risk premium was insignificant for the full period. However, during explosive volatility, investors were rewarded for taking up more risk. Moreover, we found that risk premium, leverage effects, and volatility persistence were significantly correlated. The GARCH (1,1) and TGARCH(1,1) models were found to be the best fit models to test for symmetric and asymmetric effects respectively. While the GARCH models were able to provide evidence for the stylized facts in the NSE, we conclude that the presence or absence of these features is period specific. This especially relates to volatility persistence, leverage effects, and risk premium effects. Caution should, therefore, be taken in using a specific GARCH model to forecast market return volatility in Kenya. It is thus imperative to pretest the data before any return volatility forecasting is done.