The Mediating effect of corporate governance quality on the association between audit report lag and earnings quality in NSE

Submitted in Partial Fulfillment of the Requirements for Degree of Master of Commerce of Strathmore UniversityThe purpose of this research is to establish the mediating effect of corporate governance on the association between audit report lag and earnings quality. The research aims at addressing two main research questions. First, how earnings quality influence audit report lag and second, what mediating role does corporate governance quality play on the association between earnings quality and audit report lag in non-financial companies listed on the Nairobi Securities Exchange? In this study, both primary and secondary data were used. The secondary data were obtained from companies’ audited annual reports, while a closed-ended research questionnaire was used to collect primary data. The data was analyzed in two stages. In the first stage, an association test between the audit report lag (which was measured as the number of days from the financial year-end to the date of signing the audit report) and earnings quality (which was measured as discretionary accruals as per the discretionary accruals model) was carried out. In the second stage, a mediation test to examine the mediating effect of corporate governance qualities on the association above was conducted. The association test was analyzed based on the significance of the independent variables. Although the model was significant, the t-statistic for the discretionary accruals was statistically insignificant despite there being a negative correlation between earnings quality and audit report lag, which could be interpreted as an increase in the earnings quality leads to a decrease audit report lag. For the mediation test, the R-squared, F-statistics and the t-statistics were significant. This justifies that there is a mediating effect of corporate governance quality on the association between audit report lag and earnings quality. To corroborate these findings from the secondary data, the findings from the primary data with valid Cronbach’s Alpha, provided additional evidence on the importance of the quality of corporate governance in mediating earning quality and audit report lag. While audit report lag can be easily identified, there are still difficulties in detecting earnings management. As such, these findings may act as a red flag for detecting earnings management in non-financial firms listed on the NSE. This study will be of interest to investors in identifying earnings management, regulatory bodies for detecting gaps in reporting and policymakers who would set up corporate governance policies to improve companies’ management

Bean commodity corridors scaling up production and market expansion for smallholders in Sub-Saharan Africa

More structured production, distribution, and trade are important in upgrading bean value chains for higher trade volumes, farmer incomes, and national revenue. A strategic intervention to achieve these goals efficiently and effectively involves the use of a commodity corridor approach. Commodity corridors are areas of bean intensification characterized by flows of products from production to consumption points. These intensification zones are characterized by significant bean activities that include production, distribution, and consumption, and are supported by vast networks of actors. Sub-Saharan African has a low and declining share in the global trade of agricultural products; hence, the continent is trying to incorporate geographic and regional trading blocs to align them with private- sector partnership programs. The aim of this policy direction is to use territorial comparative advantages to increase market power and share, and promote regional development, which ultimately can lead to country- specific economic development and poverty reduction. In this document, we draw on data, lessons, and experiences curated over the six years when the Pan-Africa Bean Research Alliance (PABRA) implemented the bean corridor model (under the Improving Bean Production and Marketing in Africa project funded by Global Affairs Canada) to inform how a bean corridor can be conceptualized and operationalized. The conceptualization is based on economic growth approaches in the literature and inclusive business models and tools using beans as a case. We supply evidence of bean corridors that have emerged over time, benefits that arise from a functional bean corridor, and the roles of lead firms and facilitators. Here, the bean corridor is taken as a boundary-spanning tool that can bring spatially focused, and commodity-focused development approaches together to solve persistent market failures along the bean value chain. Evidence shows that a bean corridor can emerge when there is a marketable product, for example, a preferred bean variety, and lead firm(s) and facilitator(s) to smoothen the trading process. The bean corridor then facilitates trade in large volumes of beans, stimulates public- and private- sector investments into the development of novel bean products, and increases value chain coordination efficiency. By bringing together the actors, through multi-stakeholder platforms, and harnessing information and communication technologies and digital tools, the bean corridor leads to improved market efficiency. By using the bean corridor to improve the business environment, to strengthen linkages between research and research product users (traders, processors, seed producers, farmers, etc.); and between bean farmers and buyers, and engagement with policy makers, its potential to enhance value chain efficiency (e.g., inputs and output aggregations) and ultimately to transform the largely informal ad hoc bean market to a structured bean trade has been demonstrated. This approach can find applicability in other commodities amenable to intensification driven by markets

Development and validation of a diagnostic aid for convulsive epilepsy in sub-Saharan Africa: a retrospective case-control study

Background: Identification of convulsive epilepsy in sub-Saharan Africa relies on access to resources that are often unavailable. Infrastructure and resource requirements can further complicate case verification. Using machine-learning techniques, we have developed and tested a region-specific questionnaire panel and predictive model to identify people who have had a convulsive seizure. These findings have been implemented into a free app for health-care workers in Kenya, Uganda, Ghana, Tanzania, and South Africa. Methods: In this retrospective case-control study, we used data from the Studies of the Epidemiology of Epilepsy in Demographic Sites in Kenya, Uganda, Ghana, Tanzania, and South Africa. We randomly split these individuals using a 7:3 ratio into a training dataset and a validation dataset. We used information gain and correlation-based feature selection to identify eight binary features to predict convulsive seizures. We then assessed several machine-learning algorithms to create a multivariate prediction model. We validated the best-performing model with the internal dataset and a prospectively collected external-validation dataset. We additionally evaluated a leave-one-site-out model (LOSO), in which the model was trained on data from all sites except one that, in turn, formed the validation dataset. We used these features to develop a questionnaire-based predictive panel that we implemented into a multilingual app (the Epilepsy Diagnostic Companion) for health-care workers in each geographical region. Findings: We analysed epilepsy-specific data from 4097 people, of whom 1985 (48·5%) had convulsive epilepsy, and 2112 were controls. From 170 clinical variables, we initially identified 20 candidate predictor features. Eight features were removed, six because of negligible information gain and two following review by a panel of qualified neurologists. Correlation-based feature selection identified eight variables that demonstrated predictive value; all were associated with an increased risk of an epileptic convulsion except one. The logistic regression, support vector, and naive Bayes models performed similarly, outperforming the decision-tree model. We chose the logistic regression model for its interpretability and implementability. The area under the receiver operator curve (AUC) was 0·92 (95% CI 0·91–0·94, sensitivity 85·0%, specificity 93·7%) in the internal-validation dataset and 0·95 (0·92–0·98, sensitivity 97·5%, specificity 82·4%) in the external-validation dataset. Similar results were observed for the LOSO model (AUC 0·94, 0·93–0·96, sensitivity 88·2%, specificity 95·3%). Interpretation: On the basis of these findings, we developed the Epilepsy Diagnostic Companion as a predictive model and app offering a validated culture-specific and region-specific solution to confirm the diagnosis of a convulsive epileptic seizure in people with suspected epilepsy. The questionnaire panel is simple and accessible for health-care workers without specialist knowledge to administer. This tool can be iteratively updated and could lead to earlier, more accurate diagnosis of seizures and improve care for people with epilepsy

S2 Fig -

a. Prevalence of persistent respiratory symptoms across WHO regions. b. Prevalence of persistent respiratory symptoms across income levels. c. Prevalence of persistent respiratory symptoms across age groups. (TIF)</p

Overall prevalence of PTLD.

A forest plot showing the overall prevalence of PTLD from all 30 studies involving a pooled sample size of 6050 study participants. Studies used varying methods of post-TB assessment, for this composite model if a study used more than one method, spirometry data was adopted, symptom data if no spirometry was done, and radiology data if neither spirometry nor symptom assessment was done.</p

Factors associated with persisting respiratory symptoms following TB.

Factors associated with persisting respiratory symptoms following TB.</p

Prevalence of PTLD across World Health Organisation regions.

A forest plot showing subgroup meta-analysis comparing prevalence of PTLD as a composite outcome (abnormal spirometry or persistent symptoms or abnormal radiology) in all 30 studies across five WHO regions.</p