Economic growth and socioeconomic changes have transformed nearly every aspect of childhood in China, and many are worried by the increasing prevalence of mental health issues among children, particularly depression. To provide insight into the distribution of depressive symptoms among children in China and identify vulnerable groups, we use data from the 2012 China Family Panel Survey (CFPS), a survey that collected data from a large, nationally representative sample of the Chinese population. Using the CFPS data, we construct a sample of 2679 children aged 10–15 years old from 25 provinces in China. According to our results, the incidence of depression varies by geographic area. Specifically, we find that rates of depressive symptoms are significantly lower in urban areas (14% of sample children) than in rural areas (23% of sample children). Our results also show that children from ethnic minorities, from poorer families, and whose parents are depressed are more likely to be depressed than other children. In contrast, we find that depressive symptoms do not vary by gender.

China’s rapid urbanization in the past several decades have been accompanied by rural labor migration. An important question that has emerged is whether rural labor migration has a positive or negative impact on the depressive symptoms of children left behind in the countryside by their migrating parents. This paper uses a nationally representative panel dataset to investigate whether parental migration impacts the prevalence of depressive symptoms among left-behind children in China. Using DID and PSM-DID methods, our results show that parental migration significantly increases the depression scores of 10 and 11-year-old children by 2 points using the CES-D depression scale. Furthermore, we also find that the negative effect of decreased parental care is stronger than the positive effect of increased income in terms of determining the depressive symptoms status of children in rural China.

In China, due to decades of the ‘one-child policy’ and continuous rural-urban labour migration, real population aging in rural areas is increasing more quickly than in urban areas, and the labour inputs in agricultural production are becoming ever more dependent on the elderly. Using CHARLS data, we examine the effect of health on the labour supply of rural elderly people. We construct a latent health stock index (LHSI) to eliminate measurement bias and then use this one-period lagged LHSI and the Heckman two-stage and the Bourguignon-Fournier-Gurand two-stage method to deal with the simultaneous causality of health and labour decisions and sample selectivity in model estimation. The results show that, in the overall level, the labour force participation and work time of rural elderly people increase significantly with the improvement of health. These effects on the males are sharply greater than on the females and are enhanced with age. In the subdivided agricultural and non-agricultural labour supply, health improvement is positively related with labour force participation of rural elderly and brings an employment allocation from agricultural section to non-agricultural section, especially on the males. However, as the work time, these relations are insignificant and invariant with gender and age.

This paper addresses the operating room management problem for private hospitals aimed at the high-end customer market. A patient preference-driven policy that incorporates surgeon scheduling into the surgery scheduling process is proposed to satisfy patients' personalised preferences for surgeons and surgery dates. A stochastic programming model is formulated with the objective of minimizing operating rooms' staffing costs. A column generation-based heuristic algorithm is developed to solve the integrated surgeon and surgery scheduling issue. The performance of the algorithm is tested on different scale instances. Numerical results indicate that the patient-preference driven approach can identify an effective solution to operating room scheduling that satisfies patients' preferences with only slightly increased staffing costs. Additionally, the column generation-based heuristic algorithm can obtain solutions within a 1.6% gap of the lower bound obtained by the linear relaxed problem.

Purpose: Whether training contributes to stabilizing employment among rural migrant workers in cities remains unclear. Based on this gap in the research, the purpose of this paper is to examine how on-the-job training affects rural migrant workers’ job mobility in China.Design/methodology/approach: By using randomly sampled survey data on migrant workers in Liaoning province in 2014, the authors applied a logistic model and survival analysis to explore the effect of on-the-job training on migrant workers’ job turnover and understand workers’ job change behaviour after receiving on-the-job training.Findings: The results showed that job training provided by employers can significantly reduce migrant workers’ turnover by increasing specific human capital. By contrast, training provided by the government or migrant workers themselves focuses on increasing general human capital and thus fails to reduce job turnover. Moreover, further discussion revealed that, in the trained group, those people with a short tenure and low wage in the first job, people without any skills before migration, male migrant workers, and people that work in medium-sized and large cities have a higher probability of changing jobs. These findings suggest that to tackle the high rate of job mobility among rural migrant workers, firms should entice this labour to train by adjusting their internal training mechanisms, and local governments should subsidize firms that provide on-the-job training for rural migrant workers to help share the costs and risks of training. Moreover, for sake of reducing job changing among those trained workers, firms even should take actions to protect their labour rights of migrant workers and to ensure that they receive equal treatment to their urban counterparts.Originality/value: This paper makes three contributions to the field of job mobility in China. First, it explores the mechanism between on-the-job training and rural migrant workers’ job mobility. Second, it empirically analyses the effect of on-the-job training on migrant workers’ job mobility as well as the different effects of general and specific training. Lastly, its results have important policy implications for the employment stability of rural migrant workers.