Innovation and green are the directions to promote the circular economy and environmental sustainability at the corporate level. This paper examines the impact of environmental regulation (pollution charge) on green technology innovation and the mediating role of corporate environmental responsibility. Our results indicate that: (1) Environmental regulations stimulate manufacturing enterprises’ environmental responsibility and green technology innovation. It is worth noting that corporate environmental responsibility strengthens the relationship between environmental regulation and green technology innovation. (2) Further investigation reveals that R&D expenditure and environmental investment have greatly strengthened the positive effect of environmental regulation on green technology innovation. (3) With more detailed disclosure about enterprises’ environment-related information, the more outstanding stimulation effects of environmental regulation. Discussions on the features of enterprise location have revealed that, if the goal of environmental protection is set too high or if the fiscal decentralization is too strong, implementation of environmental regulation would not achieve desirable results. Accordingly, we need to optimize the collection of environmental taxes, strengthen the enterprises’ environmental responsibility, and increase investment in R&D and environment protection. Meanwhile, the execution of environmental regulation should also take into account the institutional environment and governance features of the enterprise locations.

This paper proposes the “citizen-ecology-city” evaluation framework for urban ecological livability theoretically and studies the ecological livability of the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) empirically. In addition, we analyze the factors of urban ecological livability in a spatial dynamic panel model. The results are as follows. (1) Ecological livability levels of Macao and Hong Kong are significantly higher than the nine cities in the PRD; (2) Shenzhen and Guangzhou lead the nine cities in the PRD, while Jiangmen and Zhaoqing perform poorly; (3) GBA cities can be divided into three categories: Macao, Hong Kong, Shenzhen, and Guangzhou in the first tier; Zhuhai, Foshan, and Dongguan in the second tier; Huizhou, Zhongshan, Jiangmen, and Zhaoqing in the third tier; and (4) The ecological livability of the GBA cities has a characteristic of spatial correlation. In terms of the international value, the three-dimensional evaluation framework can apply to other bay areas in the world.

This paper aims to study the change and decomposition of multidimensional relative poverty in China. The data we use are from the China Health and Nutrition Survey (CHNS). The data cover 12 provinces in China and span a long period, from reform to precise poverty alleviation. The results show that the multidimensional relative poverty index presents a change pattern of “gradual rise (1991–2004)-decline (2004–2011)-rise again (after 2011)”. The dimensions of education, income, and employment contribute more to multidimensional relative poverty, followed by health and living standards. Multidimensional relative poverty is more severe in rural areas, central and western regions, women, and the elderly. The “incidence of poverty effect” is the main factor in the changes in multidimensional relative poverty, and its contribution is higher than the “intensity of poverty effect”.

Poverty is a critical issue in sustainable development, and the study of poverty has gradually shifted from absolute to relative poverty. This paper measures three types of relative poverty—strongly relative poverty (50% of median income), strongly relative poverty (50% of mean income), and weakly relative poverty. Then this paper decomposes the change of relative poverty into the growth component, redistribution component, and poverty line change component. Further, the intra- and inter-group decompositions of relative poverty change are carried out by considering the urban and rural population mobility components. We apply the China Health and Nutrition Survey (CHNS) data from 1989 to 2015 for an empirical study. The results show that: (1) In recent years, the change in relative poverty in China has shown a trend of low fluctuation (1989–1997), rising fluctuation (1997–2006), and high fluctuation (2006–2015). (2) In the decomposition of relative poverty change, the growth component has the most excellent effect on alleviating relative poverty, the redistribution component exacerbates the occurrence of relative poverty in most years and reduces it in a few years, and the poverty line change component offsets the poverty reduction effect of the growth component. (3) The change in relative poverty is decomposed by urban and rural sub-groups, and it is found that the population mobility from rural to urban can reduce the national relative poverty.

Urban experience can increase the ability of rural migrants to integrate into cities, thereby enhancing their settlement intentions. This paper empirically supports these findings using data from the China Migrants Dynamic Survey (CMDS). The mechanism analysis finds that urban experience promotes economic survival skills and adaptive capacity among rural migrants and enhances their willingness to settle in cities. It has significantly increased the labor market income, social activity, and interpersonal interaction of rural migrants. Compared with other cities, the urban experience of rural migrants who move to first-tier cities in their first migration significantly impacts their willingness to settle in cities. Finally, further discussion finds that the impact of urban experience on rural migrants’ settlement intention is nonlinear, with an inverted U-shaped curve. These findings can help local governments in China improve the integration ability and willingness of rural migrants to settle in cities through measures such as optimizing household registration and improving the social security system. They can also provide lessons for urbanization development in other countries.

China has eliminated absolute poverty and begun to tackle relative poverty, yet the change in relative poverty in China has been less studied. In this paper, we develop a three-component decomposition of the change in relative poverty and apply it to analyze the relative poverty in China. The change in relative poverty is decomposed into identification, growth, and redistribution components. We compare the three-component decomposition with other decomposition methods in the existing literature and show the advantages of the former. Our study, using the China Family Panel Studies (CFPS) 2010–2018 data, shows that relative poverty is rising. Examining the periods of 2012–2014, 2014–2016, and 2016–2018, we show that the three components differ in their contribution to relative poverty. The identification component rises with income growth and increases relative poverty by 8.42%, 12.19%, and 12.55%, respectively. The growth component reduces the incidence of relative poverty by 8.34%, 11.24%, and 12.18%, respectively. In comparison, the redistribution component increases the incidence of relative poverty by 2.88%, 1.12%, and 6.60%, respectively.