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Climate change is one of the main issues facing countries in sub‐Saharan Africa. Improving green productivity is essential for transitioning to low‐carbon economies and mitigating climate change in this region. The existing literature does not emphasise the role of the energy transition in green productivity growth. Yet this analysis is important given the essential role of energy in the production process and the high endowment of renewable energy sources in the area. Thus, this paper contributes to the literature by examining the effect of the renewable energy transition on green productivity growth through a convergence analysis for 35 sub‐Saharan African countries from 2000 to 2020. The results of the logt test reveal the existence of three main convergence clubs in terms of green productivity. The first club with low productivity is made up of 23 countries, the second club with average productivity contains 8 countries, and the third club with high productivity comprises 3 countries, while 1 country is divergent. The renewable energy transition is a determining factor in the formation of these convergence clubs. Indeed, the results of the ordered logit regression show that an increase in the level of the renewable energy transition has a positive impact on the probability of countries joining convergence clubs with higher green productivity. Further analysis with the Generalized Method of Moment (GMM) reveals that the critical threshold for renewable energy share in the energy mix that allows countries to converge globally toward the green productivity frontier in the long term is 32.63%. Regarding policy implications, the results highlight the need to encourage the renewable energy transition to increase green productivity in sub‐Saharan African countries. This could involve strengthening policies to promote investment in the sector (creation of green funds and/or tax incentives) and subsidies for renewable energy consumption. [ABSTRACT FROM AUTHOR]

This study aimed to examine household fuel choice behaviour and drivers of variation in fuel choice for cooking. It utilizes descriptive statistics, ordered logit model and generalized ordered logit model to analyze the influence of independent variables upon dependent variables. The result shows that, mixed fuels are the dominant sources of energy with 43.75 % followed by unclean fuel with 33.25 % and then clean fuel with 23 %. This confirms ‘households’ Fuel-Stacking behaviour. The result of the ordered logit model suggest that variables like family size, per monthly income, the gender of household head, household ownership of electric meter, ownership of housing unit, marital status, age, occupation, educational levels of household heads, and the number of the adult females are statistically significant at 1 %, 5 %, and 10 % while, place of residence and occupation (self-non agriculture) are statistically insignificant to determine fuel choice. Identifying the fuels which are chosen by households should serve as a guide for government and policymakers in the formulation and implementation of policies and strategies that will guarantee optimal access to clean energy sources. Therefore, the government should improve the supply and distribution of electric meters by subsidizing them.

Achieving urban food security before and after COVID-19 lockdown among urban households' in Ghana is key. This paper compares the pre-and post-COVID-19 lockdown food security status of urban dwellers in lockdown cities of the Greater part of Accra in Ghana using the Rasch and ordered logit model. From a sample of 340 respondents, the study found a significant difference in household food security status and predictors of food security. Prior to COVID-19 households were 'High food secure' (36.4%), but post-COVID-19 lockdown made more households 'Very low food secure' (12.35%). To combat post-COVID-19 lockdown food insecurity in urban agriculture is encouraged. [ABSTRACT FROM AUTHOR]

Purpose. This paper aims to identify the major determinants of agricultural credit and their marginal effects, along with describing the pattern of the predicted probability of getting credit from the agricultural credit cooperatives. Methodology / approach. We used a multi-stage stratified random sampling method to collect data from the paddy farmers of Kerala, India. Descriptive statistics are used to describe the profile of the farmers. Ordered logistic and probit regression models are used to model the credit categories. The authors analyzed the determinants of credit and their marginal effect, while the pattern of the predicted probability is described using tables and graphs. Results. Results show that age, household size, farming experience, and farm size significantly influence the probability of a farmer falling into a particular credit category. However, the estimated coefficients of other factors, like gender and occupation, are not statistically significant. The results from the study clearly show that relatively large paddy farms are not getting enough credit from the cooperatives, contrary to the common perception. An evaluation of the predicted probabilities shows that the very high and shallow categories are much more dispersed than the middle categories. Originality / scientific novelty. This is the first study that describes the predicted probability of credit availability pattern from the agricultural credit cooperatives to the paddy farmers. Moreover, this study describes the determinants and their marginal effects by credit category. Practical value / implications. The results indicate the probability of a farmer falling into a specific credit category based on his/her characteristics or background. The results can help them frame a strategy while approaching a credit cooperative for a loan. The inverse relationship between age and the likelihood of getting higher credit amounts requires government policy intervention. It will be hard for farmers to continue farming while aging if they do not get sufficient credit. The government must develop policies to counteract the influence of age on credit availability, like special schemes for older age groups.

The largest agrarian state in India's North-East, Assam exhibited varied growth of agrarian technology at regional level since 1950. The growth of modern technology in agriculture is expected to work as impetus to agricultural productivity and farmers' welfare. Adoption of technology such as improved seed variety and use of machine has resulted in increase in yield of winter rice. Striking difference in yield could be observed between adopters and nonadopters of technology. Ordered Logit model is applied to estimate the impacts of different factors on the adoption of agricultural technology. The result reveals that cultivated area, yield and the experience of farmers have significant positive impacts on the adoption of modern technology for the cultivation of winter rice. The findings are in support of building agrarian infrastructure and facilitation for adoption and suitable technological transformation for the enhancement of yield and sustainable agricultural progress. [ABSTRACT FROM AUTHOR]

The measurement of inequality and its determinants are major tasks within the economic literature. The main objectives of this paper are to identify patterns of convergence in the income inequality in European Union countries and to investigate the factors behind the formation of convergence clubs. For those purposes and considering the Gini index during the period 2007–2018, the club convergence approach and an ordered logit model are employed. The results show four clubs and four divergent countries. In addition, the analysis identifies certain factors, such as economic openness, public intervention and education, as the main drivers of inequality reduction. Finally, the results from the club convergence analysis for an alternative inequality measure, specifically the ratio 80:20, are similar to those achieved in the case of the Gini index. [ABSTRACT FROM AUTHOR]

As intercity buses are a mode that moves large-scale occupancy between regions, it accounts for the mode share-means for mid- to long-distance movement in South Korea. However, the study of intercity bus safety needs to be more extensive, and safety policies are carried out based on traditional probability models without considering the data characteristics of bus accidents. Therefore, in this study, the Random Parameter Ordered Logit model was applied to derive fixed parameter factors that have the same effect on the severity of intercity bus accidents and Random Parameters that consider the heterogeneity of unique attributes by accident. It also analyzed the marginal effect of intercity bus accident severity. As a result of this study, the influencing factors that reflect heterogeneity with random parameters were driver's condition: drowsiness, vehicle size: medium, crash type: vehicle–pedestrian accident, road condition: wet pavement, and log form of AADT. The random parameter ordered logit model was traditionally found to be more suitable than the ordinal logit model, which only reflects fixed factors and more reliable predictions considering the heterogeneity of accident characteristics for each observation. [ABSTRACT FROM AUTHOR]

The study examined the vulnerability of agrarian households to food insecurity in Ogun State, Nigeria. One hundred and twenty (120) agrarian households were chosen using a multistage sampling procedure. Data were gathered using a focus group discussion and a pre-tested questionnaire. Descriptive statistics, coping strategy index (CSI) and ordered logit regression were employed for data analysis. Results revealed that agrarian households, which had a mean age of 52 years, a mean household size of 7 persons, mean farm size of 1.5 ha, and a mean monthly income of N49, 508.3 ($60.66) respectively, were predominately male (60.8%). Findings from the CSI revealed that 62.5% of the agrarian households were mildly vulnerable to food insecurity. The result of the ordered logit regression analysis showed that age, household size, farm size, off-farm income, number of dependence, days of incapacitation and numbers of coping strategies adopted were the significant determinants of agrarian households' vulnerability to food insecurity (VFI). Consuming low-quality and less expensive food products, sending children under the age of 18 to work to help with household needs as well as skipping meals, among other measures, were effective coping mechanisms adopted to combat VFI shocks. The study concluded that agrarian households were at risk of food insecurity, and as a result, there was a need for special consideration in the form of significant food support and access to production inputs that would increase their productive capacity, boost their income, and assist them in escaping this vulnerability in the study area. [ABSTRACT FROM AUTHOR]

So far, studies have paid less attention to the farmer's intention in developing a waterbased crop pattern, so this article examines the relationship between the characteristics of 393 active farmers in the Jiroft plain and their willingness to accept a water-based crop pattern. Farmers were surveyed about the level of willingness to accept the proposed cropping pattern, demographic characteristics, socio-economic factors and institutional characteristics using a questionnaire with open and closed questions in the 2020 crop year. In order to achieve the research objectives, a stratified logit model was used in which the dependent variable of the research (willingness to accept the crop pattern appropriate to water resources) was ranked in five categories including 0: unwillingness to accept; 1: low acceptance; 2: willingness to moderate acceptance; 3: willingness to accept too much and 4: willingness to accept too much. The results showed that 62% of respondents tended to accept below average and only 7.9% of farmers tended to accept too much. The results showed that the variables of age, literacy level, average monthly income, personal ownership of land, access to credit and membership in farmers 'social institutions had a positive and significant effect on farmers' willingness to accept and non-payment of water input by farmers had the opposite effect. Findings showed that a variety of variables may explain the willingness of farmers to develop protective behaviors for water resources that should be considered. [ABSTRACT FROM AUTHOR]

Rural communities are more likely to encounter constraints in achieving food security and adequate nutritional supply. This study explores food security, nutritional supply, nutrient adequacy, macronutrient balance, recipes, and nutrient sources based on bi-monthly household surveys in rural villages in Northern and Southern Burkina Faso from 2019 to 2020. Food security across time and its quantity dimensions were measured using the food consumption score (FCS). Ordered logit regression showed that FCS was significantly influenced by season, region, and household characteristics such as the head's education and women's possession of personal plots. The regional differences were large: Households categorized as having "poor" diets were approximately 1% and 38% in the south and north, respectively. Nutrient adequacy was assessed by converting 24 h dietary recall into nutrient supply and comparing the results to the requirement. While macronutrient balance appeared adequate in the pooled sample, it became unacceptable when the two regions were considered separately. Most micronutrient supplies were insufficient. Cereals were the main nutrient sources, and leaves of crops and potash (additive containing potassium) were also non-negligible for micronutrient supplies. Overall, we found large regional differences in nutrition and food security, indicating that various local contexts must be considered for effective nutritional improvement. [ABSTRACT FROM AUTHOR]

A child’s ability to resist temptation is an important non-cognitive skill and associated with lifetime benefits. Using a longitudinal dataset, this study links Chinese preschoolers’ delay of gratification to their later scholastic performance during primary education. An empirical investigation is conducted to explore the potential relation between them. The results show that this personality trait, revealed at age 4–5 years by using the marshmallow experiment, has a long-lasting and positive contribution, even after accounting for students’ cognitive performance and other non-cognitive skills measured at age 10–11 years. Our findings in a developing country context are supported by evidence from developed countries.

The main purpose of this study is to investigate the extent and manner of the impact of political economy factors on the de facto exchange rate regime in developing countries and to extract implications for the political economy of the Iranian exchange rate regime. In this study, using ordered logit and probit models, we examine the impact of trade, financial, and political economy factors on the real exchange rate regime in middle-income developing countries during the period 1996-2012. The results of the research show that in the sample, an increase in the size of the economy increases the likelihood of choosing a floating exchange rate regime, and an increase in institutional quality, government strength, the power of interest groups, the level of democracy, and oil rents increases the likelihood of choosing a fixed exchange rate regime. Another conclusion is that the political economy factors have different effects on the choice of exchange rate regime in developing countries with upper-than-average incomes and developing countries with lower-than-average incomes. As a result, given that in developing countries the political economy factors have a significant impact on the choice of exchange rate regime, and since the influence of political economy factors on the choice of exchange rate regime leads to the adoption of a non-optimal currency system, policymakers in these countries need to reconsider how they choose the currency system. Also, according to the experimental results of this study, developing countries with poor institutional quality such as Iran are not able to maintain a stable exchange rate regime.

Ordinal outcomes are common in the social, behavioral, and health sciences, but there is no commonly accepted approach to analyzing them. Researchers make a number of different seemingly arbitrary recoding decisions implying different levels of measurement and theoretical assumptions. As a result, a wide array of models are used to analyze ordinal outcomes, including the linear regression model, binary response model, ordered models, and count models. In this tutorial, we present a diverse set of ordered models (most of which are under-utilized in applied research) and argue that researchers should approach the analysis of ordinal outcomes in a more systematic fashion by taking into consideration both theoretical and empirical concerns, and prioritizing ordered models given the flexibility they provide. Additionally, we consider the challenges that ordinal independent variables pose for analysts that often go unnoticed in the literature and offer simple ways to decide how to include ordinal independent variables in ordered regression models in ways that are easier to justify on conceptual and empirical grounds. We illustrate several ordered regression models with an empirical example, general self-rated health, and conclude with recommendations for building a sounder approach to ordinal data analysis. [ABSTRACT FROM AUTHOR]

Financial inclusion is vital in economic development as it empowers families and communities to meet basic needs, such as nutritious food, clean water, housing, education, and healthcare. Financial inclusion is also a tool for hedging against extreme weather events, disasters, and health crises such as the COVID-19 pandemic. Moreover, access to financial services has the potential to alleviate poverty, reduce income inequality, and stimulate economic growth and development. However, there is limited literature regarding the impact of financial inclusion at the household level. According to the latest World Bank Global Findex, the number of financially included adults has risen substantially in Tanzania due to the introduction of mobile money and baking financial inclusion. Based on Tanzania World Bank's Global Findex micro-data set for 2011, 2014, and 2017 surveys, this study uses the ordered probit regression model with endogenous treatment assignment to evaluate factors influencing financial inclusion and estimate the impact of financial inclusion on income in Tanzania. The available literature guided us in selecting the independent variables to include in the financial inclusion and impact models. The applied model allows for correcting for self-selection bias and endogenous effects associated with financial inclusion and income. Self-selection bias can occur when individuals choose whether to participate in a program based on their socioeconomic and demographic circumstances. Due to self-selection, participants often differ from nonparticipants in ways significant to the research, leading to a biased sample, which affects the generalizability of the research results. The results show that formal education and lack of money are the most crucial factor influencing financial inclusion and exclusion. Moving from financial exclusion to inclusion increased the probability of being in the higher income brackets. Personal finance education programs geared towards the most vulnerable groups would improve financial inclusion and income in Tanzania. Results from this study indicate that financial inclusion has a positive impact on income, and thus, it is crucial to enhance the scope coverage via more extensive and swift channels, such as mobile money and baking. Enhanced financial inclusion in Tanzania will lead to higher and quicker integration of the excluded community members into formal financial systems, thereby maximizing the effects of financial inclusion on the poor and the country's economic growth. [ABSTRACT FROM AUTHOR]

To adhere to health regulations and reduce the risks associated with the COVID-19 pandemic, employers, mobility operators, and travelers alike adopted new strategies such as teleworking, rigorous sanitation, and social distancing. In this research, we examine the individual-level factors contributing to transit ridership abandonment and return decisions. We utilize comprehensive survey-based data of transit users in the Chicago metropolitan area (N = 5648) collected prior to reopening. We investigate three ridership behaviors, namely (1) discontinued public transit ridership, (2) the intent to return to pre-pandemic transit ridership levels once health concerns are alleviated, and (3) the likelihood of using public transit more often if its fare systems are integrated with other mobility services such as ridehailing and micromobility. Examining the role of sociodemographics, employment characteristics, transit investment priorities, and travel behavior before and during the pandemic, this research reveals fine-grained details about transit usage decline, as well as future intentions. The results indicate that teleworking, unemployment, and vehicle access are the major factors behind discontinued transit ridership. Analysis of race, ethnicity, and gender effects reveals that vulnerable users often have a higher risk of abandonment coupled with a lower likelihood of returning. These results point to the need for transit agencies to consider the specific concerns of ethnic/racial minorities and women. Encouragingly, there is an opportunity for agencies to attract more ridership with fare integration. Several respondent segments would use transit more if fare systems are integrated with ridehailing and micromobility, highlighting the importance of lowering the barriers to accessing these mobility services. This research informs several policies that can be adopted by transit agencies and other mobility providers. We discuss the importance of an equitable return to transit, possibilities for Mobility-as-a-Service with fare integration as a starting point and stress the significance of teleworking in future transit policies. • Study pandemic abandonment of transit, intentions to return to riding transit, and likelihood of increased ridership with fare integration. • Assess the role of sociodemographics, employment characteristics, transit investment priorities, and travel behavior. • Compare the ridership return intentions by multiple transit agency types (e.g. urban/suburban, bus/rail). • Teleworking, vehicle access, racial or ethnic minority status or priority for sanitation of transit facilities impact future ridership intentions. • Discussion of how transit can attract vulnerable customer segments during the pandemic recovery phase. [ABSTRACT FROM AUTHOR]

The health and economic burdens of HIV/AIDS in low-and-middle-income countries are enormous despite global and local efforts to prevent and mitigate its effect. This study seeks to assess cadres' (or people living with HIV [PLHIV]) health-seeking behavior and its effects on their quality of life (QoL). We collected cross-sectional data from 218 HIV community cadres and 255 noncadres in 11 out of the 16 political regions in Ghana based on a modified WHOQOL-HIV-Brief and EQ-5D questionnaires. We used descriptive statistics to describe the sample and calculate the QoL scores. We also used regression analysis (ordered logit and ordinary least squares) to analyze the factors associated with the QoL of our respondents. We found that women (77%) are still disproportionally affected by HIV. Similarly, the youth, less educated and informal sector employees continue to be affected most by HIV. Factors related to QoL of PLHIV include being a community cadre, health-seeking behavior, comorbidities, and employment type. We recommend that alternative health providers be educated on the basic science of HIV/AIDS to help them offer appropriate support to PLHIV who visit them for care. Additionally, PLHIV should be supported to engage in less energy demanding employment options. [ABSTRACT FROM AUTHOR]

Sovereign credit ratings summarize the creditworthiness of countries. These ratings have a large influence on the economy and the yields at which governments can issue new debt. This paper investigates the use of a multilayer perceptron (MLP), classification and regression trees (CART), support vector machines (SVM), Naïve Bayes (NB), and an ordered logit (OL) model for the prediction of sovereign credit ratings. We show that MLP is best suited for predicting sovereign credit ratings, with a random cross-validated accuracy of 68%, followed by CART (59%), SVM (41%), NB (38%), and OL (33%). Investigation of the determining factors shows that there is some heterogeneity in the important variables across the models. However, the two models with the highest out-of-sample predictive accuracy, MLP and CART, show a lot of similarities in the influential variables, with regulatory quality, and GDP per capita as common important variables. Consistent with economic theory, a higher regulatory quality and/or GDP per capita are associated with a higher credit rating. [ABSTRACT FROM AUTHOR]

This study empirically tests whether there is evidence of convergence in ecological footprint among 189 countries for the period 1990–2017. Using the novel log (t) regression model that accommodates likely transitional heterogeneity in the panel, the results provide evidence for the divergence of ecological footprint (EF) for the world sample. A similar empirical outcome was obtained for sub-Saharan Africa (SSA), Europe and Central Asia (ECA), East Asia and Pacific (EAP), Latin America and the Caribbean (LAC), and Middle East and North Africa (MENA). Nevertheless, the study found three convergence clubs for the world sample, SSA, ECA, and LAC, while two clubs were found for EAC and MENA. Further empirical results from the ordered logit and probit model suggest initial EF and natural resource utilization are the most critical driver of club membership in SSA. Since we established three club formations, the study recommends different environmental protection policies should be adopted for the countries in these convergence clubs. It is also important for SSA governments to implement strong environmental regulations in respect of the exploitation of resources. [ABSTRACT FROM AUTHOR]

Pedestrian fatality and injury is one of the most concerning issues around the globe. The predictors for such mishaps have been investigated in the developed countries through econometric models and are proven useful techniques. Such studies in the context of developing countries, especially for urban cities, are however still very scarce. Using five years reported pedestrian crash data, this study looks into the performance of three statistical models - Multinomial Logit (MNL), Ordered Logit (OL) and Partial Proportional Odds (PPO) model while examining the impact of various attributes related to pedestrian crashes severity outcomes for Dhaka metropolitan city in Bangladesh. The comparative analysis reveals that the performance of the PPO model is relatively better for the available dataset in terms of identifying critical risk factors. Undivided roadway, heavy vehicles, unfit vehicles, adult drivers with no seat belt use, young and older pedestrians, pedestrian road crossing action are found to be associated with higher probability of fatal injuries. In contrast, one-way traffic movement, daytime, motorcycles and mid-aged pedestrians decrease the likelihood of fatal injury. Based on these identified risk factors, a combined 3-E approach has been suggested to reduce the severity levels of pedestrian in the event of crash occurrence.

The health and economic burdens of HIV/AIDS in low-and-middle-income countries are enormous despite global and local efforts to prevent and mitigate its effect. This study seeks to assess cadres' (or people living with HIV [PLHIV]) health-seeking behavior and its effects on their quality of life (QoL). We collected cross-sectional data from 218 HIV community cadres and 255 noncadres in 11 out of the 16 political regions in Ghana based on a modified WHOQOL-HIV-Brief and EQ-5D questionnaires. We used descriptive statistics to describe the sample and calculate the QoL scores. We also used regression analysis (ordered logit and ordinary least squares) to analyze the factors associated with the QoL of our respondents. We found that women (77%) are still disproportionally affected by HIV. Similarly, the youth, less educated and informal sector employees continue to be affected most by HIV. Factors related to QoL of PLHIV include being a community cadre, health-seeking behavior, comorbidities, and employment type. We recommend that alternative health providers be educated on the basic science of HIV/AIDS to help them offer appropriate support to PLHIV who visit them for care. Additionally, PLHIV should be supported to engage in less energy demanding employment options. [ABSTRACT FROM AUTHOR]

Several studies have evaluated consumer interest in olive oil as a functional food due to its multiple health benefits, but to date, no author has assessed consumers' additional premium price for a differentiated product enriched with its own polyphenols. This paper aims to investigate which predictors are related to health consciousness by assessing the willingness to pay an additional premium price for olive oil with functional properties. In addition, the study assesses how self-perceived nutritional knowledge affects price levels and interest in olive oil characteristics. The survey was carried out in Italy and the statistical analyses were conducted in two stages: the first adopted an econometric approach to evaluate which variables are related to the additional premium price for the product while in the second stage, inferential statistics were performed to obtain information on the role of self-perceived nutritional knowledge. Based on these outcomes, the prominent role of extrinsic characteristics, such as Geographical Indications (GIs), local attributes and health nutritional information emerged, reaffirming the strong link with the territory and health concerns of modern olive oil consumers. Finally, high self-perceived nutritional knowledge respondents were aware of the antioxidant properties of olive oil and registered the highest price thresholds. [ABSTRACT FROM AUTHOR]

Eucalyptus tree is expanding on farm lands of Ethiopia at an alarming rate and efforts of local authorities to control this expansion have become sources of conflict and wide spread grievances among smallholder farmers in Gurage Zone. Focus Group Discussion, key Informant Interviews as well as Household Survey were used as data collection methods. The result from the ordered logit estimation indicated households' perception to be influence by demographic and socio-economic factors such as age and educational level of household head and total land holding. Households, who have favorable perception towards eucalyptus tree, continue planting it despite the negative perception of experts and local officials and their efforts to control its expansion. The formulation and effective implementation of policy regarding eucalyptus trees and undertaking continuous awareness raising programs are essential measures needed to win the support of farmers in controlling the expansion of eucalyptus tree which is essential for a sustainable use of rural lands. [ABSTRACT FROM AUTHOR]

Abstract Background Current research on activities of daily living (ADLs) disability has mostly focused on the analysis of demographic characteristics, while research on the microcharacteristics of individuals and the macroenvironment is relatively limited, and these studies solely concern the impact of air quality on individual health. Methods This study innovatively investigated the impact of air quality on ADL disability by matching micro data of individuals from the China Health and Retirement Longitudinal Study with data of urban environmental quality from 122 cities. In this study, an ordered panel logit model was adopted for the benchmark test, and the two-stage ordered probit model with IV was used for endogenous treatment. Results This innovative study investigated the impact of air quality on ADL disability by matching individual micro data from the China Health and Retirement Longitudinal Study with urban environmental quality data for 122 cities. The results showed that air quality significantly increased the probability of ADL disability. The positive and marginal effect of air quality on moderate and mild disability was higher. Generally, the marginal effect of air quality on residents’ health was negative. In terms of group heterogeneity, the ADL disability of individuals aged over 60 years, those in the high Gross Domestic Product (GDP) group, females, and those in the nonpilot long-term care insurance group was more affected by air quality, and the interaction between air quality and serious illness showed that the deterioration of air quality exacerbated the ADL disability caused by serious illness; that is, the moderating effect was significant. Conclusions According to the equilibrium condition of the individual health production function, the ADL disability caused by a 1% improvement in air quality is equivalent to the ADL disability caused by an 89.9652% reduction in serious illness, indicating that the effect of improved air quality is difficult to replace by any other method. Therefore, good air quality can not only reduce ADL disability directly but also reduce serious illness indirectly, which is equivalent to the reduction of ADL disability. This is called the health impact.

We investigate the time variation in credit rating standards awarded to financial institutions of commercial bank credit ratings awarded by the three principal CRAs from 1990 to 2015 in a world-wide context by testing for well-defined structural shifts. We focus on the part of the ratings that cannot be accounted using publicly available information. We test whether major financial events are conditioning, ex-post such changes Distinctively in this paper's timespan our analysis covers four periods: (i) before and (ii) after the 2001–2 corporate collapses, followed by (iii) before the global financial crisis and (iv) after the global financial crisis. We find substantial differences in the assignment of bank credit ratings among the three major agencies, Moody's, Fitch, and S&P. Agencies differ both in terms of re-adjustment of ratings but also on the speed of response to the evens. All three agencies tightened ratings during the 2008 crisis and kept reducing them in its aftermath. [ABSTRACT FROM AUTHOR]

The South African smallholder sector is characterised by relatively low productivity due to persistent deterioration in soil fertility owing to declining organic matter and other essential soil nutrients. Consequently, adoption of sustainable agricultural inputs like organic fertiliser is essential. Although there is sufficient advocacy in the adoption of organic fertiliser, the economic linkage between farmers' socioeconomic factors and willingness to pay (WTP) remains under-explored. This study investigated the determinants of WTP a price premium for organic fertiliser among smallholder potato farmers using primary data collected from 189 smallholder farmers in three municipal areas in KwaZulu-Natal, South Africa, through a multi-stage sampling technique. The data was analysed using the ordered logit model and revealed that marital status, access to extension services, and knowledge of organic fertiliser usage, land ownership, livestock size and distance to the source of organic fertiliser influenced the farmers’ WTP for organic fertiliser. The study found that about 83.6% of the sampled smallholder farmers were willing to pay for organic fertiliser, while about 16.4% of them indicated that they were not willing to pay for organic fertiliser. This result justifies the prospect of commercialisation of organic fertiliser to facilitate the availability of organic fertiliser to those that are willing to pay for it. This study recommends improved access to extension services to enhance technical information dissemination and knowledge of organic fertiliser usage among smallholder farmers. Development of policies that strive to institute security of land tenure among smallholder farmers, which will encourage smallholder farmers WTP is also essential.

Some studies have quantified the extent and examined the determinants of the global multidimensional poverty index (G-MPI) which contains only three dimensions of welfare. But studies on the extent and determinants of rural multidimensional poverty index (R-MPI) which contains rural livelihood as one dimension of welfare are scarce. Hence, this study quantified the extent and examined the determinants of rural multidimensional poverty index using the Alkire–Foster method and the ordered logistic regression model, respectively. Data were gathered from 415 random sample households in southern Ethiopia. The incidence, intensity, and adjusted headcount ratio of rural multidimensional poverty are 72.3%, 57.3%, and 41.4% respectively. Besides, 7.47%, 20.24%, 30.60%, and 41.69% of households are non-poor, vulnerable, poor, and extremely poor, respectively. The living standard and rural livelihood dimensions jointly contributed 60% to rural multidimensional poverty. Fuel for cooking, electricity, and housing are the primary contributors to rural poverty from the living standard dimension, while land ownership, off-farm activity, and tropical livestock units are the leading contributors from the rural livelihood dimension to rural deprivation. Regression results showed that education, land size, tropical livestock unit, off-farm participation, and saving are negatively and significantly related to rural poverty, while dependency ratio, distance from market, distance from the road, and sickness of family members are positively and significantly related to rural poverty. Female-headed households were more deprived than male-headed households. Hence, promoting access to land, non-farm employment, markets, electricity, drinking water, and a road network would reduce rural multidimensional poverty in southern Ethiopia.

Positive externalities of education on health have been widely studied in the prior literature. However, the focus has been on the count of years of schooling rather than the levels of schooling, which is a commonly overlooked yet meaningful way of assessing the education – health relationship. Further, the role of health beliefs in determining the relation between education and health has been understudied, particularly for women. We address these two important questions by using a large‐scale household survey data from India. We find that education levels have differential impact on health beliefs and the impact is highest for individuals with higher levels of education. These findings indicate how educational interventions at lower levels can be effective in improving health beliefs to encourage appropriate health behaviour from early stages of life. [ABSTRACT FROM AUTHOR]

This study aimed to examine household fuel choice behaviour and drivers of variation in fuel choice for cooking. It utilizes descriptive statistics, ordered logit model and generalized ordered logit model to analyze the influence of independent variables upon dependent variables. The result shows that, mixed fuels are the dominant sources of energy with 43.75 % followed by unclean fuel with 33.25 % and then clean fuel with 23 %. This confirms 'households' Fuel-Stacking behaviour. The result of the ordered logit model suggest that variables like family size, per monthly income, the gender of household head, household ownership of electric meter, ownership of housing unit, marital status, age, occupation, educational levels of household heads, and the number of the adult females are statistically significant at 1 %, 5 %, and 10 % while, place of residence and occupation (self-non agriculture) are statistically insignificant to determine fuel choice. Identifying the fuels which are chosen by households should serve as a guide for government and policymakers in the formulation and implementation of policies and strategies that will guarantee optimal access to clean energy sources. Therefore, the government should improve the supply and distribution of electric meters by subsidizing them., Competing Interests: The author declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Author.)

Pedestrian fatality and injury is one of the most concerning issues around the globe. The predictors for such mishaps have been investigated in the developed countries through econometric models and are proven useful techniques. Such studies in the context of developing countries, especially for urban cities, are however still very scarce. Using five years reported pedestrian crash data, this study looks into the performance of three statistical models - Multinomial Logit (MNL), Ordered Logit (OL) and Partial Proportional Odds (PPO) model while examining the impact of various attributes related to pedestrian crashes severity outcomes for Dhaka metropolitan city in Bangladesh. The comparative analysis reveals that the performance of the PPO model is relatively better for the available dataset in terms of identifying critical risk factors. Undivided roadway, heavy vehicles, unfit vehicles, adult drivers with no seat belt use, young and older pedestrians, pedestrian road crossing action are found to be associated with higher probability of fatal injuries. In contrast, one-way traffic movement, daytime, motorcycles and mid-aged pedestrians decrease the likelihood of fatal injury. Based on these identified risk factors, a combined 3-E approach has been suggested to reduce the severity levels of pedestrian in the event of crash occurrence. • The study examines the impact of various attributes on pedestrian severity outcomes in a developing metropolis • It looks into the performance of Multinomial Logit, Ordered Logit and Partial Proportional Odds model • Divider, traffic movement pattern, vehicle types, driver and pedestrian age, pedestrian action have significant effect • Combined 3-E approach has been suggested to reduce the severity levels of pedestrian [ABSTRACT FROM AUTHOR]

• Pedestrian fatalities has been a critical issue for Victoria, in the last decade. • Driver and Vehicle characteristics and pedestrian crash injury are insightfully related. • Pedestrians' severe crashes are more likely in Dark streets and high speed limit areas. • Children and older adults are more vulnerable in pedestrian crashes. • The MNL model is better fitted on crash injury prediction models than OLR model. Introduction: The safety of pedestrians is a major concern in Victoria, Australia. Despite the considerable number of pedestrian fatalities and injuries in traffic crashes, a limited number of studies focused on pedestrian crash severity in Victoria. Methods: This study investigates and identifies the influential factors determining the severity of pedestrian injuries in traffic crashes in Victoria by using crash data from 2010 to 2019. An unordered multinomial logit model and an ordered logit model are developed for this purpose. Results: The results indicate that pedestrian crashes on weekends, in the period of 10 a.m. to 10 p.m., on dark streets, at intersections, in areas with a speed limit above 50 km/h, and on medians or footpaths are associated with a higher probability of severe and fatal injuries. Male pedestrians, children, and older adults (>59) were more likely to sustain a higher level of injury in crashes. Concerning the driver characteristics, no significant relationship was found between pedestrian injury severity and driver gender and license status, but older drivers were more likely to cause severe and fatal injuries. Pedestrian collisions with motorcycles, heavy vehicles, light commercial vehicles, bus/minibus/coach, and trams increase the probability of more severe injuries compared to cars. Moreover, older vehicles are associated with a higher probability of severe pedestrian injuries. Comparison of the model results illustrated that the MNL model was slightly better fitted on the data than the ordered logit model, but the conclusions inferred from these two models were generally similar. Practical Application: To reduce the injuries of pedestrian crashes, we recommend improving lighting conditions and sidewalk design, implementing speed reduction strategies at high pedestrian activity areas, introducing more pedestrian crossings at midblock, installing warning signs to drivers, and discouraging the use of vehicles that are more than 20 years old. [ABSTRACT FROM AUTHOR]

The 2030 Agenda of the United Nations clearly sets the inclusion of persons with disabilities in the labour market as a main goal. However, especially in care welfare systems characterized by a low level of social services, disability not only impacts the labour market participation of disabled people themselves but may also affect the labour opportunities of other members of their household. Using EU-SILC data to compute individual work intensity-as a better measure of the actual level of labour attainment-this paper aims to disentangle direct and indirect correlations between disability and labour market participation in Italian households. In confirming the negative direct correlation between disability and labour market participation, the results also show a negative indirect correlation that depends on the family relationship between the disabled person and household members. [ABSTRACT FROM AUTHOR]

The fatal rate of truck-involved crashes is increasing and crashes become more severe than passenger vehicles in recent years. Much research has been dedicated to exploring the truck crash factors while scarce research focused on the intersection scenarios. This study investigates the factors that affect the severity level of truck-involved crashes at cross- and T-intersections. Due to the unobserved heterogeneity inherent in crash data, latent class analysis is firstly conducted to divide the crash dataset into relatively homogeneous clusters. Considering the ordinal feature of the severities, general ordered logit models are subsequently developed to further explore the specific factors within each cluster. This study uses the North Carolina’s truck-involved crash at intersection data during 2005 to 2017 from the Highway Safety Information System (HSIS). The estimated parameters and associated marginal effects are combined to interpret the impact of the significant variables within specific clusters. Many factors are found to contribute to the severities, and T-intersection is found to be safer than cross-intersection. For driving behaviors, followed too closely, disregarded signs, disregarded signals, failed to yield, and exceeded speed are found to be top five factors that increase the crash severity at intersections. These results indicate that distraction and speed limits violation always result in severe injury for humans involved in the truck crashes at the intersections. The results of this research provide more reliable analysis for the impact factors of truck-involved crashes at intersections to engineering practitioners and researchers.

Abstract The purpose of the research is to evaluate the impact of different kinds of information disclosures of milk labels, investigating the interest among consumers based on their consumption behaviours and characteristics. In this research, all the actions which lead to a healthiness, become expressions of a production process, among which consumers’ food choices, purchase, preparation, and also self-production. Therefore, in the “health creation” production process, information and knowledge about food become “investments”. In this context, label disclosures become a tangible expression of this kind of “investment”. The research question is: what impact do purchase preferences and consumers’ characteristics have on their interest towards the label information provided? Several information disclosures, both mandatory and voluntary, are investigated. Therefore, some choice attributes will be analysed as indicators of the consumer’s behaviour in relation to his investment in food information. The methodology used for the analysis is an Ordered Logit. The analysis of the consumer’s behaviour has been performed by transposing Ménard’s analysis of firm corporate governance (Ménard, Agribus. 34:142–160, 2018) to the consumer as producer of welfare equity. The reduction of information asymmetry is a cost for the producer, and this research may be able to measure how much it would be convenient to invest in this reduction, based on the analysis of the consumer’s behaviour toward his personal investment in food information acquisition.

Background: Current research on activities of daily living (ADLs) disability has mostly focused on the analysis of demographic characteristics, while research on the microcharacteristics of individuals and the macroenvironment is relatively limited, and these studies solely concern the impact of air quality on individual health.Methods: This study innovatively investigated the impact of air quality on ADL disability by matching micro data of individuals from the China Health and Retirement Longitudinal Study with data of urban environmental quality from 122 cities. In this study, an ordered panel logit model was adopted for the benchmark test, and the two-stage ordered probit model with IV was used for endogenous treatment.Results: This innovative study investigated the impact of air quality on ADL disability by matching individual micro data from the China Health and Retirement Longitudinal Study with urban environmental quality data for 122 cities. The results showed that air quality significantly increased the probability of ADL disability. The positive and marginal effect of air quality on moderate and mild disability was higher. Generally, the marginal effect of air quality on residents' health was negative. In terms of group heterogeneity, the ADL disability of individuals aged over 60 years, those in the high Gross Domestic Product (GDP) group, females, and those in the nonpilot long-term care insurance group was more affected by air quality, and the interaction between air quality and serious illness showed that the deterioration of air quality exacerbated the ADL disability caused by serious illness; that is, the moderating effect was significant.Conclusions: According to the equilibrium condition of the individual health production function, the ADL disability caused by a 1% improvement in air quality is equivalent to the ADL disability caused by an 89.9652% reduction in serious illness, indicating that the effect of improved air quality is difficult to replace by any other method. Therefore, good air quality can not only reduce ADL disability directly but also reduce serious illness indirectly, which is equivalent to the reduction of ADL disability. This is called the health impact. [ABSTRACT FROM AUTHOR]

The study aims to investigate the factors that are associated with fatal and severe vehicle–pedestrian crashes in Great Britain by developing four parametric models and five non-parametric tools to predict the crash severity. Even though the models have already been applied to model the pedestrian injury severity, a comparative analysis to assess the predictive power of such modeling techniques is limited. Hence, this study contributes to the road safety literature by comparing the models by their capabilities of identifying the significant explanatory variables, and by their performances in terms of the F-measure, the G-mean, and the area under curve. The analyses were carried out using data that refer to the vehicle–pedestrian crashes that occurred in the period of 2016–2018. The parametric models confirm their advantages in offering easy-to-interpret outputs and understandable relations between the dependent and independent variables, whereas the non-parametric tools exhibited higher classification accuracies, identified more explanatory variables, and provided insights into the interdependencies among the factors. The study results suggest that the combined use of parametric and non-parametric methods may effectively overcome the limits of each group of methods, with satisfactory prediction accuracies and the interpretation of the factors contributing to fatal and serious crashes. In the conclusion, several engineering, social, and management pedestrian safety countermeasures are recommended. [ABSTRACT FROM AUTHOR]

In this paper, we analyze the extent to which process or product innovation accentuates or mitigates the corruption obstacle for Tunisian firms. Using firm-level data from the World Bank Enterprise Survey conducted in 2013, we empirically test how innovation accentuates or mitigates the corruption obstacle. We show that innovation has a negative and statistically significant effect on the corruption obstacle. Besides, we prove that competition and the obstacle to corruption are negatively related. This result teaches that the Tunisian firms face a rent-shifting corruption. [ABSTRACT FROM AUTHOR]

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Background: The study attempted to understand rural Bangladesh's health information, awareness level, and preventive measures in the Coronavirus disease -19 (COVID-19) pandemic. Methods: A cross-sectional survey by face-to-face interview was conducted with rural people from 14 June 2020 to 13 August 2020. An ordered logistic regression model was employed for data analysis. A total of 3,007 people (Female = 55.97%; Male = 44.03%) participated in the survey who met the inclusion criteria. Results: The demography of respondents revealed that a significant portion of villagers were within the ages 21-30 (26.80%), had primary education (23.88%), unemployed (31.73%), and middle class (56.17%). The most common and influential used media to know about the Coronavirus disease were electronic media and relative/family/friend/neighbors. Change of demography created a spectacular difference in public awareness level and hygiene practice. Female, illiterate, poor, and age above 60 were comparatively less aware of seven essential facts about the disease. There was no mentionable difference in personal hygienic practices due to sex. But particpants who were aged 51-60 years, graduates or postgraduates, unmarried, government or non-government employees and middle class exhibitedthe best hygiene practice over other features. Invariably, the education level of rural people had a positive effect on awareness and preventive measures. Conclusions: Overall, the government and policymakers must identify vulnerable groups whose awareness and hygienic practices are not at the optimum level. Afterward, the government and related organizations should take necessary measures immediately to protect these groups from COVID-19 threats until the complete immunization.

BACKGROUND The study attempted to understand rural Bangladesh's health information, awareness level, and preventive measures in the Coronavirus disease -19 (COVID-19) pandemic. METHODS A cross-sectional survey by face-to-face interview was conducted with rural people from 14 June 2020 to 13 August 2020. An ordered logistic regression model was employed for data analysis. A total of 3,007 people (Female = 55.97%; Male = 44.03%) participated in the survey who met the inclusion criteria. RESULTS The demography of respondents revealed that a significant portion of villagers were within the ages 21-30 (26.80%), had primary education (23.88%), unemployed (31.73%), and middle class (56.17%). The most common and influential used media to know about the Coronavirus disease were electronic media and relative/family/friend/neighbors. Change of demography created a spectacular difference in public awareness level and hygiene practice. Female, illiterate, poor, and age above 60 were comparatively less aware of seven essential facts about the disease. There was no mentionable difference in personal hygienic practices due to sex. But particpants who were aged 51-60 years, graduates or postgraduates, unmarried, government or non-government employees and middle class exhibitedthe best hygiene practice over other features. Invariably, the education level of rural people had a positive effect on awareness and preventive measures. CONCLUSIONS Overall, the government and policymakers must identify vulnerable groups whose awareness and hygienic practices are not at the optimum level. Afterward, the government and related organizations should take necessary measures immediately to protect these groups from COVID-19 threats until the complete immunization. [ABSTRACT FROM AUTHOR]

Some studies have quantified the extent and examined the determinants of the global multidimensional poverty index (G-MPI) which contains only three dimensions of welfare. But studies on the extent and determinants of rural multidimensional poverty index (R-MPI) which contains rural livelihood as one dimension of welfare are scarce. Hence, this study quantified the extent and examined the determinants of rural multidimensional poverty index using the Alkire–Foster method and the ordered logistic regression model, respectively. Data were gathered from 415 random sample households in southern Ethiopia. The incidence, intensity, and adjusted headcount ratio of rural multidimensional poverty are 72.3%, 57.3%, and 41.4% respectively. Besides, 7.47%, 20.24%, 30.60%, and 41.69% of households are non-poor, vulnerable, poor, and extremely poor, respectively. The living standard and rural livelihood dimensions jointly contributed 60% to rural multidimensional poverty. Fuel for cooking, electricity, and housing are the primary contributors to rural poverty from the living standard dimension, while land ownership, off-farm activity, and tropical livestock units are the leading contributors from the rural livelihood dimension to rural deprivation. Regression results showed that education, land size, tropical livestock unit, off-farm participation, and saving are negatively and significantly related to rural poverty, while dependency ratio, distance from market, distance from the road, and sickness of family members are positively and significantly related to rural poverty. Female-headed households were more deprived than male-headed households. Hence, promoting access to land, non-farm employment, markets, electricity, drinking water, and a road network would reduce rural multidimensional poverty in southern Ethiopia. [ABSTRACT FROM AUTHOR]

Investigating the acquisition timeframe of battery-electric vehicles (BEVs) could help identify the conditions needed to entice fleet operating entities (FOEs) to lean towards early fleet electrification. This paper addresses this issue by estimating ordered logit models with data collected from an online survey. The results suggest differences in the acquisition timeframes of government and corporate FOEs. In general, corporate FOEs tend to have a shorter acquisition timeframe. The significant factors for a shorter acquisition timeframe include the size and location of the FOEs, availability of on-site charging infrastructure, and existence of regulatory imperatives in fleet procurement. The propensity of a shorter acquisition timeframe for car fleets is higher for FOEs with an economically driven attitude. Similarly, the acquisition of utility fleets is shorter for government FOEs with economically driven attitudes and corporate FOEs with early adopter attitudes. Likewise, the acquisition of pickup truck fleets is shorter for corporate FOEs with obligatory attitudes. [ABSTRACT FROM AUTHOR]