Search Results (75)

Digital inclusive finance has become an important policy instrument for promoting inclusive growth and decent employment. Using matched data from the China Micro- and Small-Enterprise Survey (CMES) and the Peking University Digital Financial Inclusion Index, this study applies a bivariate Probit model to 3263 micro- and small enterprises (MSEs) across 28 Chinese provinces to examine how digital inclusive finance relates to MSEs’ labor hiring decisions, distinguishing between formal and informal employment and exploring the underlying mechanisms. Digital inclusive finance is positively associated with formal employment and negatively associated with informal employment in MSEs. Mediation analysis shows that credit constraints are an important transmission channel, accounting for 9.17% and 10.58% of the associations with formal and informal employment, respectively. The breadth of coverage and depth of use of digital inclusive finance are positively associated with formal employment and negatively associated with informal employment, whereas the degree of digitalization exhibits the opposite pattern. Digital inclusive finance also alleviates supply-side credit constraints faced by MSEs but shows no significant relationship with demand-side constraints. These findings offer policy implications for promoting inclusive and decent employment in MSEs. Full article

After the 2021 military coup in Myanmar, many people sought safety, decent work, and social protection in neighboring Thailand. This study examines how legal documentation status and Sense of Place (SOP) are associated with the workplace retention intentions of irregular Myanmar migrant workers in Mae Sot, Thailand. SOP is conceptualized through three key dimensions: emotional bonds to the surrounding environment (place attachment), the extent to which the place meets everyday needs (place dependence), and the way migrants identify with their host context (place identity). To explore these dynamics, we adopted an explanatory sequential mixed-methods approach, surveying 101 respondents between January and April 2024 and subsequently conducting in-depth interviews with 30 individuals between June and July 2024. Given the sensitivity of irregular migration and undocumented legal status, obtaining survey responses was challenging because many potential participants were concerned about privacy, identification, and possible legal exposure. Quantitative data were analyzed using descriptive comparisons, bivariate association tests with Goodman-calibrated minimum Bayes factors, LASSO-assisted variable screening, principal component analysis, and Bayesian mixed-effects ordinal probit models. The descriptive and bivariate results show that legal documentation status is positively associated with all SOP dimensions, job satisfaction, and willingness to remain in the current job. In the candidate model comparison, the Bayesian specification without legal status showed slightly better predictive performance than the corresponding specification with legal status. The primary five-category Bayesian mixed-effects model indicated positive conditional associations of Job Satisfaction, Place Attachment, and the structural workplace index with willingness to stay. It also indicated heterogeneity in the Place Attachment association across observed job tenure groups; this pattern is interpreted as a cross-sectional between-group difference rather than as evidence of individual change over time. Complementary Bayesian sensitivity analyses evaluate the multidimensional SOP construct, the incremental predictive contribution of legal status, sensitivity to alternative priors, and model diagnostics. The qualitative interviews further show that legal documentation is widely perceived as enabling broader employment opportunities, safer access to basic services, employer support, labor rights protection, and reduced exposure to exploitation. Overall, this study highlights the complementary roles of legal recognition, workplace satisfaction, and emotional rootedness in shaping migrant retention, offering implications for decent work, migrant well-being, reduced inequalities, and sustainable labor and migration policies in Thailand’s border regions, particularly in relation to SDG 8 and SDG 10. Full article

Bioenergy crops are widely regarded as a promising approach to support renewable energy production, diversify farm income, and enhance land-use efficiency. Despite these potential benefits, adoption rates remain low, and empirical understanding of landowners’ decision-making processes is still emerging. This study examines landowners’ interest in and likelihood of adopting bioenergy crops, explicitly differentiating between early-stage interest and near-term adoption intentions. Survey data from 207 landowners are analyzed using a bivariate probit model to identify key factors influencing both outcomes. The results reveal a marked disparity between expressed interest and adoption likelihood, with a significantly greater proportion of landowners indicating interest than those willing to adopt in the near term. Economic orientation increases adoption interest by 9.5 percentage points, while identity orientation increases adoption likelihood by 6.6 percentage points. Determinants such as increased awareness, land size, experience, and participation in conservation programs exert varying influences across different decision stages. These findings suggest that stated interest and stated near-term adoption likelihood represent related but distinct dimensions of adoption readiness, shaped by different economic, identity-based, and institutional factors. Effective promotion of bioenergy crops requires more than general awareness campaigns. Policies should combine financial incentives, technical assistance, market development support, and outreach strategies that present bioenergy crops as compatible with landowners’ economic goals, stewardship values, recreational uses, and long-term attachment to their land. Full article

This study applies the bivariate probit model to a panel of Chinese listed advanced manufacturers to investigate the relationship between tax incentives and firms’ decision on export and R&D. Estimations show that VAT refund and income tax deduction are positively related to firms’ decision on exporting and starting R&D, respectively. Regarding firms’ export decisions, VAT refund is associated much greatly with R&D firms’ decisions on becoming exporters than non-R&D firms’ decisions on becoming exporters. However, the relationship between tax deduction and firms’ R&D decisions depends on firm size. For large firms, tax deduction is associated relatively greatly with exporters in starting R&D activity than with domestic firms in starting R&D activity, whereas, for small firms, tax deduction is associated much more greatly with domestic firms in starting R&D activity than with exporters in starting R&D activity. The study suggests that the relationship between tax incentives and firms’ decisions on becoming exporters and R&D firms varies depending on firms’ status and size. Full article

Informal public transportation remains the backbone of urban mobility in many developing cities. While these systems offer flexible and affordable services, they are often associated with safety issues, unreliability, congestion, and environmental impacts. Consequently, transitioning travelers toward formal public transportation is a key objective for sustainable transport planning. This study investigates travelers’ willingness to shift from their current travel modes to a proposed Metro system in Alexandria, Egypt. The analysis uses stated preference data collected through interviews that presented respondents with multiple service scenarios. A correlated random parameters bivariate probit model with heterogeneity in means is estimated to capture interdependence between responses. The results reveal strong and statistically significant cross-equation error correlations, confirming that decisions are not independent and supporting the use of a joint modeling approach. Empirical results indicate that willingness to shift is influenced by socio-demographic characteristics, trip attributes, and current travel conditions. Female travelers are more sensitive to waiting time, while low-income and older individuals are less likely to shift across scenarios. Physical accessibility, especially walkability to and from stations, emerges as the most influential factor in encouraging adoption. These findings provide policymakers with actionable insights for designing inclusive, accessible, and sustainable public transportation systems. Full article

This research aimed to investigate livestock owners’ willingness to pay (WTP) for a hypothetical livestock vaccination program in southern Ethiopia. We used both primary and secondary data. The former data were collected from 377 livestock farmers. We used descriptive statistics and a seemingly unrelated bivariate probit model to analyze the data. The double-bounded contingent valuation format was used within a seemingly unrelated bivariate probit model to identify factors influencing WTP for livestock vaccination. It was found that the average WTP for sheep and goat vaccination was 0.38 USD (United States of America dollar) yearly, while for cattle and oxen vaccination, it was 0.64. Factors such as the household head’s education, sex, and age; annual income; total livestock holdings; and farm size affected farmers’ WTP for sheep and goat vaccination in both initial and follow-up scenarios. Market access, farm experience, and access to credit also influenced WTP for cattle and oxen vaccination across both bid values. We suggest that improving socioeconomic factors, such as household well-being and access to credit services, is vital because these elements directly influence a household’s capacity to invest in livestock health and productivity. Establishing clear vaccination rates, with vaccine costs aligned to the average household income, is recommended. Full article

Prior studies have typically analyzed the injury severity of bus or taxi passengers at the crash level or single-vehicle level, neglecting vehicle-level interdependence between them. To address the gap, this research sets out to analyze the factors contributing to the vehicle-level injury severities of transit bus–taxi crashes, with consideration of their interdependence and heterogeneities. The random-parameters bivariate probit model, which can capture both unobserved heterogeneity and within-crash correlation between bus and taxi injury outcomes, was advocated for the joint analysis. In the model, the factors related to the two vehicles and their drivers, together with other factors (e.g., roadway, environment, and crash configuration), were used as the explanatory variables. A total of 3404 two-vehicle bus–taxi crash records in Hong Kong, China, from 2009 to 2019 were used for model estimation. The results indicate that taxi driver age, taxi age, crash location, and collision manner resulted in heterogeneous effects on bus injury severity, and the time of day yielded a heterogeneous effect on taxi injury severity. In addition, bus driver error and street light resulted in fixed yet moderate (less than 6%) effects on bus injury severity, while taxi driver gender, speed limit, rainfall, and collision manner resulted in fixed effects on taxi injury severity, where female drivers and front collisions significantly increased the likelihood of fatality and severe injury with their marginal effects more than 20%. Based on the findings, tailored strategies pertaining to safety education, law enforcement, vehicle safety devices, and traffic management and control were proposed to mitigate crash outcomes involving public buses and taxis. Full article

For various reasons, individuals sometimes cannot go on trips. These are known as unrealized trips. In this study, we focus on discretionary trips, such as those for shopping and leisure, and analyze the factors that lead to their lack of realization due to insufficient mobility and transportation services. Based on survey data collected in Japan from populations of various sizes, K-prototypes clustering was conducted, and respondents were classified into three groups: those who only travel by private car, those with multiple transportation options, and transportation-disadvantaged individuals. Notably, the transportation-disadvantaged group exhibited a higher frequency of unrealized trips and was present in both urban and rural areas. Estimation results of the zero-inflated bivariate ordered probit (ZIBOP) model revealed that younger and lower-income individuals were more likely to experience unrealized trips. Moreover, railway frequency and last service time of bus were significant factors in urban areas, while bus service levels played a key role in rural areas. These findings suggest that “transportation-disadvantaged” individuals should be defined not only as those without a car or driver’s license but also as those who lack alternative mobility options. Full article

Rural–urban student migration during the compulsory education stage is a transitional phenomenon in China’s socio-economic development and a crucial issue for achieving the goal of urban–rural integration. This paper, grounded in theoretical analysis, constructs a “willingness-capacity-behavior” framework. Based on field survey data from 916 rural households and in-depth interview materials from County D, Province X, China, this study employs a bivariate Probit model and qualitative analysis methods to explore the driving factors and formation mechanisms of rural households’ rural–urban student migration decisions. The results indicate that rural households’ decisions regarding rural–urban student migration are jointly influenced by migration willingness and migration capacity. Only households with both migration willingness and migration capacity can actualize migration behavior. Migration willingness is derived from a cost–benefit analysis and involves joint decision-making by both parents, significantly influenced by parental personal characteristics and the student’s individual characteristics. The intermediate barriers to rural–urban student migration require certain migration capacities to be overcome, which are mainly influenced by family resource endowment and parental personal characteristics. Full article

Promoting municipal solid waste (MSW) sorting is critical to advancing sustainable and low-carbon urban development. While existing research often focuses separately on external policy tools or internal behavioral drivers, limited attention has been given to their joint effects within an integrated framework. This study addresses this gap by analyzing micro-survey data from 1983 residents across 34 prefecture-level and above cities in China, using a bivariate probit model to examine how policy tools and policy perception—both independently and interactively—shape residents’ active and passive compliance with MSW sorting policies. The findings reveal five key insights. First, the adoption and spatial distribution of policy tools are uneven: environment-type tools dominate, supply-type tools are moderately deployed, and demand-type tools are underutilized. Second, both policy tools and policy perception significantly promote compliance behaviors, with policy cognition exerting the strongest effect. Third, differential effects are observed—policy cognition primarily drives active compliance, whereas policy acceptance more strongly predicts passive compliance. Fourth, synergistic effects emerge when supply-type tools are combined with environment-type or demand-type tools. Finally, policy perception not only directly enhances compliance but also moderates the effectiveness of policy tools, with notable heterogeneity among residents with higher cognitive or emotional alignment. These findings contribute to a deeper understanding of compliance mechanisms and offer practical implications for designing perception-sensitive and regionally adaptive MSW governance strategies. Full article

We investigate the impact of significant life events on two critical health outcomes: insomnia and obesity. Using data from the Household, Income, and Labour Dynamics in Australia (HILDA) survey, we focus on significant life events experienced in the preceding 12 months. To model these health outcomes jointly, we employ a bivariate random effects probit panel data model and a longitudinal random effects panel data model whose outcomes can be a combination of discrete/categorical and continuous variables. Estimating these random effects panel data models is challenging because the likelihood is an integral over the latent individual random effects. In addition, the models often have a large number of predictors. In this paper, Bayesian inference is carried out using a particle Metropolis within a Gibbs sampler, which is particularly well suited for statistical models with latent variables. Additionally, within this inference framework, we integrate a Hamiltonian Monte Carlo (HMC) step to sample the high-dimensional vector of regression coefficients efficiently. The HMC step enables faster convergence and improved mixing of the Markov chain. Our article contributes to a better understanding of how stress-related life events shape health outcomes and demonstrates the advantages of combining particle Metropolis within Gibbs and HMC in the estimation of complex panel data models. Full article

Access to credit plays an important role in the adoption of modern agricultural practices, such as better seeds, pesticides, and fertilizers, as well as in the sustainable utilization of land by smallholder farmers. This study explores the dynamics of smallholders’ access to and utilization of informal credit to manage local farming systems. The data were collected from rural households in the Dir Kohistan mountainous region of Pakistan in 2021. A bivariate probit model was employed to analyze the data from 300 randomly selected farming households. Our findings indicate that a significant proportion of respondents (70%) reported having access to informal credit, with 65% actively utilizing credit to bolster the economic viability of their farms. This study reveals various strategies that farmers employ in response to credit constraints. The majority of farmers (69%) prioritize meeting their own farm/household needs. Social networks, particularly friends, emerge as key sources of informal credit (58.1%). The results of the bivariate probit regression analysis identify positive relationships with fellow farmers and neighbors/relatives, along with a lower perceived risk, as the most significant factors influencing access to and utilization of informal credit. Therefore, our study recommends the promotion of relationships and linkages among farmers through facilitated networking events, introducing risk mitigation measures and promoting financial literacy programs to empower smallholder capacities on the credit market. Policymakers are urged to recognize the role of social relationships and consider policies that promote community credit practices for the overall financial well-being of farmers, especially in more isolated mountain areas. Full article

(1) Background: Most nations struggle to close significant income gaps between high and low earners. While the adoption of farm machinery rental services and off-farm employment may be beneficial, it is unclear whether jointly applying both approaches can raise income levels in rural households or help narrow the income gap within the farm sector. This study investigated scenarios involving both participation in farm machinery rental markets and in off-farm work, analyzing their varied impacts on household incomes based on survey data from 1027 rice producers in rural China. (2) Methods: We employed a two-stage econometric procedure encompassing a bivariate ordered probit model with an endogeneity-corrected unconditional quantile regression model. (3) Results: Rice farmers often simultaneously rent farm machinery services and engage in off-farm work. Both activities positively affect their household incomes; however, these effects vary across different income levels. Renting farm machinery provides greater marginal benefits for lower-income households, while off-farm employment has a stronger impact on higher-income households. Farm machinery rental services appear to benefit disadvantaged households more than off-farm employment opportunities do. (4) Suggestions: To enhance the welfare of lower-income households, policymakers should focus on expanding access to farm machinery rental services. Full article

Incident clearance time (ICT) is impacted by several factors, including crash injury severity. The strategy of most transportation agencies is to allocate more resources and respond promptly when injuries are reported. Such a strategy should result in faster clearance of incidents, given the resources used. However, injury crashes by nature require extra time to attend to and move crash victims while restoring the highway to its capacity. This usually leads to longer incident clearance duration, despite the higher amount of resources used. This finding has been confirmed by previous studies. The implication is that the relationship between ICT and injury severity is complex as well as correlated with the possible presence of unobserved heterogeneity. This study investigated the impact of injury severity on ICT on Louisiana’s urban interstates by adopting a random-parameter bivariate modeling framework that accounts for potential correlation between injury severity and ICT, while also investigating unobserved heterogeneity in the data. The results suggest that there is a correlation between injury severity and ICT. Importantly, it was found that injury severity does not impact ICT in only one way, as suggested by most previous studies. Also, some shared factors were found to impact both injury severity and ICT. These are young drivers, truck and bus crashes, and crashes that occur during daylight. The findings from this study can contribute to an improvement in safety on Louisiana’s interstates while furthering the state’s mobility goals. Full article

Background: Cyberbullying and nighttime phone use are independently detrimental to sleep and psychological wellbeing, but whether in combination they might be more disruptive remains unknown. Methods: Students aged 7–19 years (N = 53,734) completed a survey measuring sleep duration, nighttime phone use, cyberbullying, and psychological distress. Results: Across stratification variables of gender (F/M) and age group (primary/secondary-school-aged children), bivariate ordered probit regression revealed that being cyberbullied and nighttime phone use were independent predictors of both increased psychological distress and obtaining <8 h sleep. Nighttime phone use was observed to moderate the relationship between cyberbullying and sleep in both primary- and secondary-school-aged girls and boys and, likewise, between cyberbullying and psychological distress, especially in secondary-school-aged boys. Notably, the moderation effect was such that the impact of nighttime phone use was lower in children who were compared with those who were not cyberbullied. This may be a ceiling effect due to the high number of cyberbullied children reporting shortened sleep and higher levels of psychological distress. Discussion: The present findings point to a possible role of nighttime phone use as a moderator of the effect of cyberbullying on sleep and psychological wellbeing. There is a need for future studies to better explore more directly the effects of cyberbullying during the nighttime. Full article