Unconditional quantile regressions, earnings disparity and gender discrimination in post-transformation of urban China

Market-oriented economic reform has gone through several key stages to bring substantial changes to current Chinese economy. It has accelerated after 1992, and meets the pattern transformation of economic development in 2002. During this dramatic and complicated economic transitional process, some issues caused people’s attention included the questions as: how does the earnings distribution change between genders from early market economy to post market economy; how do education, work experience, marriage and other factors affect gender earnings and what is the difference in internal group of women. In this paper, it will be used the data of the Chinese household income projects in 2002 and 2007 to analyse earnings disparity between genders and inner woman group. The unconditional quantile regression finds that comparing with past, the negative effect on earnings of marriage and taking care of child has much decreased, especially to women. However, high return rate to education of female workers is not as significant as before, the rate of work experience even fall faster. Along with the gender earnings gap increasing, the unexplained gap (discrimination gap) also increased over time, and is particularly pronounced for the lower and higher earnings group of women

Unconditional quantile regressions, earnings disparity and gender discrimination in post-transformation of urban China

Market-oriented economic reform has gone through several key stages to bring substantial changes to current Chinese economy. It has accelerated after 1992, and meets the pattern transformation of economic development in 2002. During this dramatic and complicated economic transitional process, some issues caused people’s attention included the questions as: how does the earnings distribution change between genders from early market economy to post market economy; how do education, work experience, marriage and other factors affect gender earnings and what is the difference in internal group of women. In this paper, it will be used the data of the Chinese household income projects in 2002 and 2007 to analyse earnings disparity between genders and inner woman group. The unconditional quantile regression finds that comparing with past, the negative effect on earnings of marriage and taking care of child has much decreased, especially to women. However, high return rate to education of female workers is not as significant as before, the rate of work experience even fall faster. Along with the gender earnings gap increasing, the unexplained gap (discrimination gap) also increased over time, and is particularly pronounced for the lower and higher earnings group of women

Variations in village migration profiles in rural China： an analysis based on the second national agricultural census data

Relatively little attention is paid to variations in rural migration at the village level even though labor supplying villages present considerable diversity in economic and development profiles. This paper examines the relationships between labor and household migration at the village level and the factors associated with different migration patterns through an analysis of data from China’s Second National Agricultural Census. The study identified four types of village migration profiles based on labor and household migration data from 4,482 villages in 10 counties across five provinces. Typical characteristics of each type villages are highlighted and implications for rural researchers and policy makers are discussed

Three essays on the discourse and consequences of rural-urban migration in China

Rural-urban migration in China is the largest human movement in the history of the world in terms of quantity. Rural-urban migrants make great contributions to urban economy and rural development in China. Yet, they usually lack formal supports in both urban and rural areas. The thesis consists of three essays related to rural-urban migration, looking at the discourse and consequences of rural-urban migration in China. The thesis augments the study of migration, social network, and human capital. The first essay in the Chapter 2 is about how job contact network affect rural-urban migrants' wages. In the nationally representative household data from the 2008 wave of Rural Urban Migration in China (RUMIC), nearly two thirds of rural-urban migrants found their employment through family members, relatives, friends or acquaintances. Using a switch regression approach, we find evidence of positive selection effects of the use of networks on wages. Users of networks tend to be older, to have migrated longer ago and to be less educated. In addition, married workers and those from villages with more out-migrants are more likely to use networks, while those without local residential registration status are less likely. Controlling for selectivity, we find a large negative impact of network use on wages. Using job contacts brings access to urban employment, but at the cost of markedly lower wages. The second essay in the Chapter 3 provides a four dimensional job quality index for rural-urban migrants, looking at the effect of job contact network on job quality. The multidimensional job quality index has captured job reality, combining information on earnings, working time, job stability, and work-related social insurances in one index. By using data of RUMIC 2008 and employing the endogenous switching regression for ordered outcomes, we find unobserables that affect the use of network also impact the job quality of the non-users of network. The positive selectivity does not exist in users of network. We demonstrate that the use of social network brings low job quality for rural-urban migrants, especially for the users of network. The findings are robust to a range of alternate measures of the job quality index, and to different identification methods. The third essay in the Chapter 4 explores the effects of the rural school consolidation on the living arrangement of rented accommodation for students and how rented accommodation affects students' academic performance in China. It is the first paper –to examine the effect of rented accommodation on children’s academic performance and to use a double robust estimator with multivalued treatments on this topic. Using a survey of 9,071 Grades 4 and 5 students in 133 primary schools in Shaanxi Province in 2013, we find that one quarter of students are rented accommodation near their schools. Rented accommodation results from students living long distances from schools, the unavailability of local schools and the low quality of schools near their home villages. Overall, rented accommodation brings students better academic performance, especially for boys. The study indicates that rented accommodation might offer another way to avoid the negative effects of school merge policy and boarding schools

A dynamic learning method based on the Gaussian process for tunnel boring machine intelligent driving

Introduction: The application of intelligent learning methods to the mining of characteristics and rules of time-series data has gained increasing attention with the rapid development of deep learning. One critical application of such methods is the intelligent assistant driving of tunnel boring machines (TBMs), for which the optimization of driving parameters is essential to improve construction efficiency. However, existing prediction models for TBM parameters are “static” and cannot dynamically capture parameter evolution during real-time driving cycles.Methods: In this study, we propose a novel dynamic learning model for TBM parameters by introducing the Gaussian process to address this problem. The model can learn decision-making experiences from historical driving cycles, dynamically update the model based on small sample data from current driving cycles, and simultaneously achieve driving parameter prediction. We focused on real-time prediction of TBM parameters in a tunnel project in western China.Results: The results show that the average relative errors of predicted total thrust and torque values were 1.9% and 2.7%, respectively, and the prediction accuracy was higher than that of conventional models such as random forest and long short-term memory. The model fully exploited updating of small samples of parameters, reducing the average time cost of the model to 29.7 s, which satisfies the requirements of efficient application.Discussion: The dynamic learning strategy of time-series data adopted in this study provides a reference for other similar engineering applications. The proposed model can improve the prediction accuracy of TBM parameters, thus facilitating the optimization of driving parameters and enhancing the construction efficiency of tunnels.Conclusion: In summary, this study establishes a dynamic learning model of TBM parameters that can dynamically capture parameter evolution and achieve accurate real-time driving parameter prediction. The proposed model can contribute to the development of intelligent assistant driving of TBMs and similar engineering applications

Glycyrrhetinic acid regulates impaired macrophage autophagic flux in the treatment of non-alcoholic fatty liver disease

Macrophages are involved in hepatocyte steatosis and necroinflammation and play an important role in the pathogenesis of non-alcoholic fatty liver disease (NAFLD). Impaired autophagy function (decreased autophagy or blocked autophagic flow) leads to cell damage and death and promotes NAFLD progression. The experimental and clinical research of glycyrrhetinic acid (GA) in the treatment of NAFLD has gradually attracted attention with clear pharmacological activities such as immune regulation, antiviral, antitumor, antioxidant, liver protection, and anti-inflammatory. However, the effects of GA on the STAT3-HIF-1α pathway and autophagy in macrophages are still unclear, and its mechanism of action in the treatment of NAFLD remains to be further elucidated. We constructed a NAFLD mouse model through a high-fat and high-sugar diet to investigate the therapeutic effects of GA. The results showed that GA reduced weight, improved the pathological changes and hepatic lipid deposition of liver, and abnormally elevated the levels of serum biochemical (AST, ALT, TG, T-CHO, LDL-C, and HDL-C) and inflammatory indexes (IL-1β, IL-4, IL-6, MCP-1, and TNF-α) in NAFLD mice. Further examination revealed that GA ameliorates excessive hepatic macrophage infiltration and hepatocyte apoptosis. The results of the cell experiments further elaborated that GA modulated the PA-induced macrophage STAT3-HIF-1α pathway and ameliorated impaired autophagic flux (blockade of autophagosome–lysosome fusion) and overactivation of inflammation. Excessive hepatocyte apoptosis caused by the uncontrolled release of inflammatory cytokines was also suppressed by GA.ConclusionThis study demonstrated that GA could regulate the STAT3-HIF-1α pathway of macrophages, ameliorate the impaired autophagy flux, and reduce the excessive production of inflammatory cytokines to improve the excessive apoptosis of liver cells, thus playing a therapeutic role on NAFLD

The impact of job contact networks on wages of rural–urban migrants in China: a switching regression approach

In nationally representative household data from the 2008 Chinese Rural to Urban Migration Survey, nearly two thirds of rural–urban migrants found their employment through family members, relatives, friends or acquaintances. This paper investigates why the use of social network to find jobs is so prevalent among rural–urban migrants in China, and whether migrants face a wage penalty as a result of adopting this job search method. Using a switch regression approach, we find evidence of positive selection effects of the use of networks on wages. Users of networks tend to be older, to have migrated longer ago and to be less educated. In addition, married workers and those from villages with more out-migrant are more likely to use networks, while those without local residential registration status are less likely. Controlling for selectivity, we find a large negative impact of network use on wages. Using job contacts brings access to urban employment, but at the cost of markedly lower wages

100 essential questions for the future of agriculture

Publication history: Accepted - 8 March 2023; Published online - 11 April 2023.The world is at a crossroad when it comes to agriculture. The global population is growing, and the demand for food is increasing, putting a strain on our agricultural resources and practices. To address this challenge, innovative, sustainable, and inclusive approaches to agriculture are urgently required. In this paper, we launched a call for Essential Questions for the Future of Agriculture and identified a priority list of 100 questions. We focus on 10 primary themes: transforming agri-food systems, enhancing resilience of agriculture to climate change, mitigating climate change through agriculture, exploring resources and technologies for breeding, advancing cultivation methods, sustaining healthy agroecosystems, enabling smart and controlled-environment agriculture for food security, promoting health and nutrition-driven agriculture, exploring economic opportunities and addressing social challenges, and integrating one health and modern agriculture. We emphasise the critical importance of interdisciplinary and multidisciplinary research that integrates both basic and applied sciences and bridges the gaps among various stakeholders for achieving sustainable agriculture. Key points Growing demand and resource limitations pose a critical challenge for agriculture, necessitating innovative and sustainable approaches. The paper identifies 100 priority questions for the future of agriculture, indicating current and future research directions. Sustainable agriculture depends on interdisciplinary and multidisciplinary research that harmonises basic and applied sciences and fosters collaboration among different stakeholders