Logit Regression Model Research Articles

The effect of smokeless tobacco (SLT) excise taxes on SLT use among youth

BackgroundSmokeless Tobacco (SLT) use prevalence among youth in the United States (US) is comparable to youth prevalence of cigarette smoking. However, it is in general understudied compared to cigarettes and draws less attention nowadays compared to e-cigarettes (ECs). AimWe estimate the own- and cross-tax elasticities of SLT use among US youth and explicitly test how SLT use changes in response to taxes on SLT, cigarettes, ECs, and beer. MethodsWe standardized SLT taxes for chewing tobacco, moist snuff, dry snuff, and snus, and computed average SLT taxes. We implemented a logit regression model within the state- and year-fixed effects framework. ResultsA 10 % increase in SLT excise taxes reduced youth SLT use by 4 % (p < 0.01). This result is primarily driven by males, Whites, multiple non-Hispanic races, other races, and individuals living in non-Appalachian states. In addition, a 10 % increase in cigarette taxes increases youth SLT use by 8 % (p < 0.05), suggesting substitutional effects. A 10 % increase in EC and beer taxes reduce SLT use by 0.5 % and 2.4 % (p < 0.01), respectively, suggesting complementary effects. ConclusionRaising excise taxes on SLT products can effectively curtail their usage among the youth population. Furthermore, increasing EC and beer taxes reduces youth SLT use. However, an increase in cigarette taxes leads to an unintended consequence of promoting SLT use among youth. In addition, increasing SLT taxes does not appear to significantly impact the disparities in youth SLT use by whether living in Appalachian states. Future research is needed to assess whether SLT taxes reduce disparities in use by rural/urban divisions.

THE IMPACT OF ELECTRIC POWER OUTAGE ON THE PROFITABILITY OF SMALL BUSINESSES IN NIGERIA: A CASE STUDY OF GWAGWALADA TOWN

This study examined the impact of electric power outages on the profitability of small businesses in Nigeria, using 50 randomly selected small businesses in Gwagwalada town as a case study. A Logit regression model was adopted, incorporating a mix of qualitative and quantitative variables. The Maximum Likelihood (ML) estimation method was utilized in estimating the Logit model. Findings from the estimated Logit model showed that electric power outages had a negative impact on the profitability of small businesses in Gwagwalada town, while small businesses' expenses on alternative electricity power supplies had a positive impact on profitability. However, both electric power outages and small businesses’ expenses on alternative electricity power supplies in Gwagwalada town had an insignificant impact on the profitability of the small businesses. Based on the findings of the study, it was recommended, among other things, that the government should undertake a national demand study to determine the exact electricity requirements to meet demand in the short, medium, and long terms. Furthermore, an integrated least-cost system expansion plan should be developed for the efficient deployment of the Nigerian electricity industry in the medium and long terms. There is also a need for diversification of electricity generation to improve the security of supply, as well as the development of capacity to generate electricity closer to demand centers to reduce technical losses. Additionally, the government should explore and develop measures to ensure the long-term supply of gas for electricity generation.

Assessing differences among persistent, episodic, and non- high-need high-cost hospitalized children in China after categorization by an unsupervised learning algorithm

BackgroundHigh-need, high-cost (HNHC) patients are a major focus of international healthcare reform. However, research on HNHC children in China remains limited. This study aims to classify HNHC pediatric patients, analyze the differences among groups, and explore the factors influencing HNHC status.MethodsData were obtained from a retrospective observational cohort of hospitalized children in Shanghai, China from 2017 to 2023. K-means clustering, one of the unsupervised learning algorithms, was employed to classify patients according to their HNHC status. Descriptive statistical analysis and the Kruskal-Wallis H test were used to describe and test the differences among different groups, with the logit regression models to analyze the predictors.Results688,131 hospitalized children were classified into three groups: 1,871 persistent HNHC, 32,539 episodic HNHC, and 653,721 non-HNHC. Significant differences were observed among these groups. Persistent HNHC patients have significantly higher costs and longer HNHC durations compared to episodic and non-HNHC patients, who were more likely to be aged 30 days to 1 year or 13–18 years, female with only one type of health insurance, and leukemia was the most prevalent and costly disease. They exhibited distinct healthcare utilization patterns, including emergency admissions, higher surgery rates, longer hospital stays, more frequent hospitalizations, and a preference for tertiary and specialized hospitals in city centers. Multiple influencing factors of persistent HNHC versus episodic HNHC and non-HNHC were identified.ConclusionThis study provides valuable insights into the classification, characteristics, and influencing factors of persistent, episodic, and non-HNHC hospitalized children in China. Persistent HNHC patients warrant targeted interventions to improve health outcomes and reduce healthcare costs. Enhanced medical coverage for key diseases, high-quality healthcare services tailored to their needs, and early interventions are crucial.

Spatial Analysis of Drug-Prone Areas in Jakarta to Enhance City Resilience

Resilience has emerged as a central theme in urban planning, offering a strategic framework to manage city development while promoting sustainability. This is particularly important for Jakarta as it ranks among the world's significant cities highly susceptible to diverse challenges and disruptions. This includes vulnerability to drug crime cases. As one of the efforts to overcome vulnerability, it is necessary to analyze drug-prone areas in Jakarta based on urban villages. The purpose of this study is to analyze the spatial distribution of drug-prone areas in Jakarta using Geographic Information Systems (GIS) and to analyze the role of factors determining the level of drug-prone areas in Jakarta province by applying an ordinal logit regression model. The results of this research show that almost all independent variables have no significant impact on the level of drug-prone areas. The result shows that the presence of foreigners has a significant impact on the level drug prone areas. The research findings recommend tighter monitoring of the presence of foreigners.

Adoption and impacts of hermetic storage on household food insecurity among maize producers’ organizations in Tanzania

We utilize a unique dataset comprising 1180 households affiliated with maize producers' organizations (POs) in the Rukwa and Ruvuma regions of Tanzania to analyze the adoption and impacts of hermetic storage technologies (HSTs) on the quantity of stored maize, measured in kilograms (QSM), and the Household Food Insecurity Access Scale (HFIAS). The study employs the logit and endogenous switching regression models to generate results. We find that, among other factors, the presence of HST vendors in the local community and training on proper HST usage are crucial in the adoption of HSTs among POs. Additionally, the usage of storage pesticides is negatively and significantly correlated with HST adoption. This suggests that farmers employing chemical insect pest control methods are less likely to adopt HSTs. The adoption of HSTs is shown to increase maize storage quantities by 40% and decrease household food insecurity by 43%. Further analysis based on the gender of the household head demonstrates that both female- and male-headed households benefit equally from the adoption of HSTs. The results advocate for the promotion of HSTs as a viable solution to mitigate household food insecurity among members of maize POs in Tanzania.

Determinants and Constraints of Access to Credit by Poultry Egg Farmers in Ogun State Nigeria

Access to credit is crucial for the advancement of the poultry industry in Nigeria, yet a significant portion of poultry farmers lack access to formal credit sources. This study investigates determinants and constraints to credit access among poultry egg farmers in Ogun State, based on data collected from 180 farmers using a multi-stage sampling technique. Descriptive statistics and a Logit regression model were employed for analysis. About 33.3% of the farmers were within the age range of 41-50, poultry farmers of 62.2% within the region were more of male farmers while 75.6% of the farmers were educated up to tertiary level. Only 45% of respondents had credit access, with varying sources: 19.8% from commercial banks, 37% from cooperatives, 18% from microfinance banks, 2.5% from the Bank of Agriculture, 6.2% from government sources, and 12.3% from private organizations. The Logit model revealed that farming experience and flock size significantly influence credit access (p&lt;0.01). For each year of farming experience, there is a 4.8% increase in the likelihood of credit access. Similarly, for each unit increase in flock size, there is approximately a 0.04% rise in credit access likelihood. Descriptive statistics highlight constraints to credit access: lack of awareness (5.1%), absence of collateral (30.3%), lack of interest (5.1%), loan denial (12.1%), high interest rates (27.2%), regulatory hurdles (8.1%), and inadequate documentation (12.1%). It is recommended that policymakers and financial institutions develop tailored credit products for poultry farmers, addressing specific challenges such as collateral requirements and high interest rates, this is because once financial barriers are removed production is likely to improve. Additionally, enhancing farmer awareness of available credit options and simplifying application processes can improve credit accessibility in the sector.

Exploring the Motives Behind the Adoption of Climate Change Adaptation Strategies among Farmers in the Czech Republic

Climate change threatens agriculture in the EU and is a primary issue discussed in the European Green Deal within the Common Agricultural Policy. Central and Eastern European countries are particularly prone to climate change effects, such as droughts and extreme weather. Therefore, agriculture in Central and Eastern Europe is expected to be increasingly affected by shifting climatic patterns. This study examines the motivation for adopting adaptation strategies derived from climate-smart agriculture among farmers in the Czech Republic. We drew particular attention to analyzing the influence of farm-level and information source variables on the adaptation behavior of Czech farmers. The dataset comprises 358 respondents who were asked about climate change adaptation through a quantitative survey. We analyzed the collected data via descriptive statistics and binary logit regression models. The analysis results reveal a high degree of awareness and a diversified usage of climate change adaptation strategies among the respondents. The close linkage between perceived profitability and the willingness to adapt to climate change requires policymakers to communicate economic benefits within this context further. Information sources, such as topic-specific journals, research institutions, and field training, positively influenced the adaptation rates among the sample. Therefore, we recommend focusing on these media channels to communicate targets set within the European Green Deal.

ASSESSMENT OF FEMALE YOUTH PARTICIPATION IN AGRICULTURAL LIVELIHOOD GENERATING ACTIVITIES IN GWAGWALADA AREA COUNCIL, ABUJA, NIGERIA

This study examines female youth participation in agricultural livelihood generating activities in Gwagwalada Area Council, Abuja. The objectives of the study were to: examine the extent of female youth participation in agricultural livelihood generating activities and the income generated, determine factors influencing female youth participation in agricultural livelihood generating activities, and identify major constraints faced by female youth participating in agricultural livelihood generating activities. A multistage sampling procedure was used to select 133 female youths from 13 registered youth associations with 10 from each group in (4) peri-urban communities of the study area. Structured questionnaire was used to collect data while descriptive statistics and Logit regression model were used to analyze the data. The results showed that 30.1% and 14.3% of the respondents were engaged in crop and poultry production and generated an average income of ₦420,093.02 and ₦216,000.00 respectively while 3.0% and 4.5 only were engaged in crop produce processing and poultry meat and egg marketing and generated ₦29,250.74 and ₦14,166.67, respectively. The logit regression results indicated that factors influencing female youth participation in agricultural livelihood generating activities include age, education status, household size, income, occupation, and distance. Also, the major constraints hindering participation were inadequate access to land (43.6%), inadequate access to finance (41.6%) and high cost of production (16%). While the study indicates that a significant portion of female youths is engaged in crop and poultry production, their overall participation in agricultural activities is limited. The study provides critical insights into the potential of agriculture as a viable solution to youth unemployment in Nigeria. The study recommends implementing policies to improve land access for female youths, including land reform initiatives that prioritize youth ownership and leasing options. Additionally, it suggests exploring strategies to reduce production costs through input subsidies, partnerships with agricultural suppliers, and community-based resource-sharing initiatives.

EFFECTS OF HEALTH EXPENDITURE ON FOOD SECURITY STATUS OF RURAL HOUSEHOLDS IN OGUN STATE, NIGERIA

The study assessed the effect of health expenditure on the food security status of rural households in Ogun State, Nigeria. Multistage sampling procedure was used to select 120 rural households in the study area. Data was collected from the respondents with the aid of a semi-structured questionnaire complemented with an interview guide. Descriptive statistics, food security index, cost of illness procedure and binary logit regression model were the analytical techniques used for data analysis. Findings from the study revealed that majority (79.2%) of the respondent were male, married (90.8%), with a mean household size of 5 persons. Also, the mean age of the respondents was found to be 54 years with most of them involved in farming as their major occupation. Findings also revealed that majority of the rural households suffered from various illnesses such as malaria, waist/back pain, fever, high blood pressure, rheumatism and other illnesses with an average estimated cost of illness (₦45, 973.68 per month). The results of the food security status of the rural households revealed that a higher percentage (53.3%) of the rural households were food insecure. Factors found to significantly affect the food security status of the rural households were cost of illness (p&lt;0.1) and other socio-economic variables such as education (p&lt;0.1), income (p&lt;0.05) and sex of the household head (p&lt;0.01). Therefore, this study recommends that government should subsidize the cost of drugs and other medical expenses for poor households particularly those in the rural areas in order to reduce their financial burden on health care and increase their economic access to food.

SOCIO-ECONOMIC DETERMINANTS OF INTEGRATED SOIL FERTILITY MANAGEMENT (ISFM) PRACTICIES CHOICE AMONG MAIZE FARMERS IN ADAMAWA STATE, NIGERIA

This study was carried out to analyzed socio-economic determinants of Integrated Soil Fertility Management (ISFM) practices choice among maize farmers in Adamawa State, Nigeria. Using a multi-stage sampling procedure, 206 maize farmers were selected and interviewed using a structured questionnaire. Descriptive statistics and multinomial logit regression models were used to analyze the data collected. Findings revealed that majority of the farmers (about 60%) fell within the 20-40 years and they were predominantly male (62.1%), married (82.0%), and had a secondary education (40.3%). Farmers operated on an average farm size of 1.70 hectares. Majority of the maize farmers in the study area used intercropping with legumes (94%), organic manure (87%) and improved maize seed (79%) ISFM practices, the least practiced ISFM among the farmers were minimum tillage, crop residue retention and use of crop rotation. Socio-economic factors that were significant (P &lt; 0.05) and positively influenced ISFM practices used among maize farmers were annual income, education level, and household size. Meanwhile gender (sex) have negative and significant (P &lt; 0.05) influence on minimum tillage practice by the maize farmers. The study concludes on moderate use of ISFM practices among maize farmers in the study area. It was therefore be recommended that organized farmer’s programmes should be targeted toward educating the farmers on ISFM practices benefits and improving their income so as to facilitate adoption of ISFM practices for sustainable farm operation.

Examining the Interrelation Between Microcredit, Entrepreneurship and Women’s Empowerment: An Insight into the Effectiveness of Pradhan Mantri Mudra Yojana (PMMY)

The present research unleashes the interrelation between microcredit, entrepreneurship and women’s empowerment in the context of Pradhan Mantri Mudra Yojana (PMMY). In light of this, a structured questionnaire designed to capture the study’s features was given to woman respondents who were residents of the six administrative regions of Haryana in order to gather their responses. The study takes into account 360 respondents. Primary data were collected from July 2023 to March 2024. Logit and ologit regression models were used to evaluate how strongly the chosen variables related to women’s employability. Wilcoxon sign test, a non-parametric test, has been used to determine whether the well-being of the woman respondents differed between the two stages (pre and post Mudra loan). The outcomes of the study revealed that there is a positive interconnection between microcredit, entrepreneurship and women’s empowerment. Further, there has been a considerable increase in the respondents’ economic, social, political and psychological empowerment when compared to the pre- Mudra loan phase. Moreover, the results showed that credit assistance under PMMY schemes helps in job creation.

Hold the chair: the link between short-term exposure and the managerial change in an emerging market during the pandemic

PurposeThis paper aims to study the effect of short-term firm-level exposure on managerial change during the COVID-19 pandemic in the Chinese economy. Such a link is not explored in the existing COVID-19 and resource-based theory (RBT) literature.Design/methodology/approachThe logit regression model is utilized to examine the effect of short-term exposure on the probability of managerial change in the Chinese economy. Logit models based on coarsened exact matching (CEM) are also used in the robustness checks part of the study. The results are robust to different specifications.FindingsThe obtained findings show that short-term exposure has a significantly positive effect on the probability of managerial change during the pandemic.Research limitations/implicationsUnder the RBT approach, this study sheds new light on the relationship between short-term financial exposure and managerial change under uncertainty during the pandemic.Practical implicationsC-Suite executives need to be prepared for short-term sudden shocks. According to the findings of the study, the relationship between short-term sudden shocks and short-term financial exposure is a factor that C-suite executives should pay attention to.Social implicationsShort-term sudden shocks can support managerial change, pushing society into uncertainty and negatively affecting the private sector. In this context, it has a structure that can amplify uncertainty.Originality/valueIn the existing COVID-19 literature, the effect of short-term exposure on the probability of managerial change is under researched, especially in the emerging markets-based RBT and COVID-19 literature. The present study offers an insight into the link between short-term exposure and the probability of managerial change during the pandemic.

Determinants of Access to Bank Credit by Smallholder Agricultural Households in Uganda: Evidence from UNHS 2019/2020

Agricultural credit plays a significant role in boosting cash and food crop production for household consumption, domestic and foreign markets. The purpose of this study was to investigate the determinants that affect smallholder farmer’s access to bank credit in Uganda. The study used data from the Uganda National Household Survey 2019/2020 (UNHS). The study utilized a logit regression model for the analysis of data. The findings from the model showed that farmer’s access to bank credit in Uganda was positively and significantly influenced by sex of the household head, income level of the household head, marital status of the household head, age of the household head and ownership of a bank savings account. The study’s conclusions led to the development of key policy recommendations. These include promoting a savings culture through various initiatives, providing incentives such as special savings accounts or matching deposit programs, creating customized banking products to carter to farmers needs and offering free tertiary education to graduates of Universal Primary Education, Universal Secondary Education, and Universal Post O Level Education and Training

Factors influencing calving difficulty and gestation length in dairy cows inseminated with beef sires

Producing calves with higher economic value by utilizing semen from beef breeds in dairy herds (Beef-on-Dairy, BoD) has become more common in recent times. Such crossbreed calves promise better carcass conformation and higher consumer acceptance due to the better flavor, but the widespread adaptation of BoD requires careful consideration of the sire breed to maximize the benefits. In this regard, two major traits of interest are calving difficulty and gestation length due to associated costs. In this study, 3,966 BoD calves from crossing Holstein dams with beef sires of the breeds Angus (n = 811), Belgian Blue (n = 2841), Limousin (n = 169) and Wagyu (n = 145) from 122 farms were evaluated to determine differences in calving difficulty and gestation length using binary logit and linear regression models. Lowest calving difficulty was observed for Wagyu crossbreds while Limousin crossbreds had the highest calving difficulty incidences. Selected sires from Angus and Belgian Blue breeds were also compared using chi-square analysis for differences in calving difficulty. The risk of calving difficulty was 1.94 times higher for male calves. Heifers had a significantly higher risk for calving difficulty when compared with the multiparous cows in the study. Calves with higher birth weight and longer gestation length were more prone to calving problems. For gestation length, Angus crossbreds had the shortest gestation (280.2 d), while the longest gestation (287.6) was observed in Limousin crossbreds. To maximize the benefits of the BoD breeding strategy, selecting appropriate sire breeds and within-breed sire selection for economically important traits, such as birth weight, appropriate gestation length, and reduced calving difficulty, may provide a viable solution.

Comparing methods for risk prediction of multicategory outcomes: dichotomized logistic regression vs. multinomial logit regression

BackgroundMedical outcomes of interest to clinicians may have multiple categories. Researchers face several options for risk prediction of such outcomes, including dichotomized logistic regression and multinomial logit regression modeling. We aimed to compare these methods and provide guidance needed for practice.MethodsWe described dichotomized logistic regression, multinomial continuation-ratio logit regression, which is an alternative to standard multinomial logit regression for ordinal outcomes, and logistic competing risks regression. We then applied these methods to develop prediction models of survival and neurodevelopmental outcomes based on the NICHD Extremely Preterm Birth Outcome Tool model. The statistical and practical advantages and flaws of these methods were examined. Both discrimination and calibration of the estimated logistic models of dichotomized outcomes and continuation-ratio logit model were assessed.ResultsThe dichotomized logistic models and multinomial continuation-ratio logit model had similar discrimination and calibration in predicting death and survival without neurodevelopmental impairment. But the continuation-ratio logit model had better discrimination and calibration in predicting neurodevelopmental impairment. The sum of predicted probabilities of outcome categories from the dichotomized logistic models could deviate from 100% substantially, ranging from 87.7 to 124.0%, and the dichotomized logistic model of neurodevelopmental impairment greatly overpredicted low risks and underpredicted high risks.ConclusionsEstimating multiple logistic regression models of dichotomized outcomes may result in poorly calibrated predictions for an outcome with multiple ordinal categories. Multinomial continuation-ratio logit regression produces better calibrated predictions, constrains the sum of predicted probabilities to 100%, and has the advantages of simplicity in model interpretation, flexibility to include outcome category-specific predictors and random-effect terms for patient heterogeneity by hospital. It also accounts for mutual dependence among multiple categories and accommodates competing risks.

Empirical Study on the Influence of Internet Use on the Employability of Local College Students

Based on the data of China Family Panel Studies (CFPS) in 2020, this paper analyzes the impact of Internet use on the employability of local college students through OLS and logit regression models. The study found that the Internet has become an important tool for local college students to improve their employability. Students who actively participate in online learning, use career recruitment platforms and social media to expand career networks in local colleges and universities show stronger competitiveness in terms of professional skills, comprehensive quality and job search skills. The importance of Internet use to work, learning and information channels has a significant impact on the employability of local college students, and has a significant moderating effect. Through heterogeneity analysis, it is found that the impact of Internet use on the employability of local college students in eastern China is significantly higher than that in central and western China : the employability of college students with urban household registration is higher than that of local college students with rural household registration, and the employability of female local college students is lower than that of male local college students. Therefore, this study suggests that local colleges and universities should further guide students to make rational use of Internet resources and strengthen network literacy education, so as to better adapt to the employment market demand and promote high-quality employment of graduates.

Determinants of Youth Unemployment in Nepal

Both developed and developing countries are facing youth unemployed problems. The main objective of the study is to identify the determinants of youth unemployment in Nepal, using secondary data. For empirical analysis, the study uses multivariate Logit regression model to identify the determinants of youth unemployment. The logistic model shows that the sample variables like time spend in farm, ever-married, communication, completed school year, training have positive relationship with probability of being youth unemployed whereas urban, house ownership, male, household size, Koshi Pradesh, Bagmati Pradesh, Gandaki Pradesh, Lumbini Pradesh, Karnali Pradesh and Sudurpaschim Pradesh have negative relationship with proability of being youth unemployed. The sample variables like as time spend in farm, completed school year, Koshi Pradesh, Bagmati Pradesh, Gandaki Pradesh, Lumbini Pradesh, Karnali Pradesh and Sudurpaschim Pradesh are significant at 1 percent level and other explanatory variable like urban, ever-married, house ownership, communication, male, training, household size are not significant but they are important determinants of youth unemployment. This study suggests that more investment on education, improve agriculture sector, emphasis on regional balance and consider the determinant factors.

An Assessment of Mental Health Challenges of Lesbian, Gay, Bisexual, and Transgender College Students during the COVID-19 Pandemic.

Collegiate mental health continues to be a worrisome public health concern among college students in the U.S. The unprecedented COVID-19 pandemic has caused an upward trend of mental health crises, especially among lesbian, gay, bisexual, and transgender (LGBTQ+) college students. The objective of this study was to assess the mental health statuses, attitudes towards disease control and mitigation measures, and coping strategies among this vulnerable group. A web-based survey was conducted at a medium-sized public university in the mid-Atlantic region during the summer and fall of 2021 when COVID-19 was still a major public health concern. The survey was distributed through the listservs of the college and was advertised through campus-wide social media. Descriptive and inferential statistics including a t-test for the differences in group means and a logit regression model for comparing the groups were used. Our final sample is composed of 611 students with 79% of the respondents identifying as straight, and 20% in the LGBTQ+ group. Our results showed that LGBTQ+ students exhibited higher levels of anxiety and fear compared to the non-LGBTQ+ groups. Also, a large proportion of LGBTQ+ students were negatively impacted by the pandemic as compared to the non-LGBTQ+ groups (p = 0.05), while they generally have more positive views on the public health measures to alleviate the adverse impacts from COVID-19 (p = 0.001). Public health emergency management should adopt appropriate strategies and adapt their services to support the mental health needs of LGBTQ+ students. Our study highlighted the need to design tailored health promotion programs and enhance support systems for LGBTQ+ college students during similar emergencies.

Can female CEOs improve corporate environmental, social and governance performance?

Purpose In the context of the severe global challenges posed by climate and environmental issues, this paper aims to explore the connection between female Chief Executive Officers (CEOs) and the level of sustainable development in companies. This study aims to investigate the impact of female CEOs on corporate ESG performance and provide a detailed analysis of the underlying mechanisms. Design/methodology/approach This study uses a sample of listed companies from 2010 to 2021, as reported by Bloomberg. This study uses logit regression models to test hypotheses and conduct robustness tests using the generalized method of moments, propensity score matching and heckman two statge tests. Findings The research findings indicate that female CEOs can enhance a company’s ESG performance, primarily by elevating the level of green innovation and engaging in more philanthropic activities. When environmental uncertainty is high, the risk-averse attitude of female CEOs may diminish the enhancement of ESG performance. However, granting a higher proportion of equity to female CEOs incentivizes risk-taking, thereby strengthening the improvement of ESG performance. Further analysis reveals that the impact of female CEOs on ESG performance is more significant in non-state-owned enterprises, high-pollution industries, and companies with low financing constraints. Research limitations/implications The authors have shown that two key ways in which female CEOs enhance a company’s ESG performance are by increasing the level of green innovation and assuming more social responsibility. Nonetheless, this remains a shortcoming of this work, opening a door for future research to examine and enrich. There may be other possible mechanisms explaining the influence of female CEOs on corporate ESG performance. More research is warranted about the CEO’s additional traits, which were not considered in this study but may have an impact on a company’s ESG performance. Finally, while the analysis has delved into the moderating effects of external factors such as environmental uncertainty and CEO ownership on the influence of female CEOs on corporate ESG performance, there is room for exploring whether other factors also play a moderating role in future studies. Practical implications First, the findings of this study highlight the beneficial societal and economic effects of choosing female CEOs. The inclination to take on social responsibility and care for the environment are both higher among female CEOs. Furthermore, the authors have also discovered that female CEOs possess unique advantages in promoting corporate sustainability and enhancing ESG standards. This can contribute to breaking down stereotypes about gender roles in the workplace. Finally, this research shows that organizational heterogeneity and market risks have an impact on female CEOs’ capacity to improve company ESG performance. Originality/value A significant innovation of this paper lies in its unique focus on the connection between female CEOs and corporate ESG performance, along with the underlying mechanisms. Against the backdrop of sustainable development, the paper integrates social gender theory, upper echelon theory and agency theory into a comprehensive framework, shedding light on the influence of female CEOs on ESG performance and the associated mechanisms.

Health outcome convergence and the roles of public health financing and governance in Africa.

Progress in health outcomes across Africa has been uneven, marked by significant disparities among countries, which not only challenges the global health security but impede progress towards achieving the United Nations' Sustainable Development Goals 3 and 10 (SDG 3 and SDG 10) and Universal Health Coverage (UHC). This paper examines the progress of African countries in reducing intra-country health outcome disparities between 2000 and 2019. In other words, the paper investigates the convergence hypothesis in health outcome using a panel data from 40 African countries. Data were sourced from the World Development Indicators, the World Governance Indicators, and the World Health Organization database. Employing a non-linear dynamic factor model, the study focused on three health outcomes: infant mortality rate, under-5 mortality rate, and life expectancy at birth. The findings indicate that while the hypothesis of convergence is not supported for the selected countries, evidence of convergence clubs is observed for the three health outcome variables. The paper further examine the factors contributing to club formation by using the marginal effects of the ordered logit regression model. The findings indicate that the overall impact of the control variables aligns with existing research. Moreover, governance quality and domestic government health expenditure emerge as significant determinants influencing the probability of membership in specific clubs for the child mortality rate models. In the life expectancy model, governance quality significantly drives club formation. The results suggest that there is a need for common health policies for the different convergence clubs, while country-specific policies should be implemented for the divergent countries. For instance, policies and strategies promoting health prioritization in national budget allocation and reallocation should be encouraged within each final club. Efforts to promote good governance policies by emphasizing anti-corruption measures and government effectiveness should also be encouraged. Moreover, there is a need to implement regional monitoring mechanisms to ensure progress in meeting health commitments, while prioritizing urbanization plans in countries with poorer health outcomes to enhance sanitation access.