The economic uncertainty caused by COVID-19 has led governments around the world to attach more importance to green innovation to accomplish their carbon reduction schemes. To improve the green innovation encouraging effect of an environmental policy system, this study introduces a unit progressive carbon tax on the basis of a green innovation subsidy to discuss the synergy green innovation effect between them. We set up a dynamic evolutionary game model to analyze the respective influences of green innovation subsidies and an environmental policy system containing a unit progressive carbon tax on Low Carbon Technology (LCT) heterogeneous enterprises’ endogenous green innovation strategies. The Evolutionary Stable Strategy analysis of dynamic game models demonstrate that there does exist a synergy green innovation effect between green innovation subsidies and unit carbon taxes. The numerical simulation shows that the synergy green innovation effect of green innovation subsidies and carbon taxes contains both an overlapping policy effect and a more significant green innovation stimulating effect on enterprises with high LCT. Additionally, the introduction of a carbon tax will increase enterprises’ affordability on the green innovation cost coefficient. Furthermore, introducing a unit progressive carbon tax would also create additional stimulation for enterprises to pursue a larger carbon reduction amount for the carbon emission cost-saving advantage. Based on the synergy green innovation effect mentioned above, we also investigate the policy implications of varying the tax rate and subsidy proportion in different situations.

The Seventh National Population Census, recently conducted in 2020, reported the most up-to-date information on the size, structure, and distribution of China’s population. The results showed that the gender imbalance in China is still severe compared with the international standard. With the aim of understanding what has contributed to China’s gender imbalance, this study examined a range of potential influencing factors and measured the extent to which they have affected China’s sex structure. We gathered data from 3100 citizens (100 surveys from each provincial-level administrative region in mainland China); the useful response rate was 87.5% (2713/3100). We relied on statistical analysis to investigate the phenomenon of male preference in China and used a logit regression to analyze the factors associated with this result. We inspected the factors associated with the perception according to gender, age, annual income, living location, educational level, nationality, family contribution, the ideology of being supported by sons, social status, ability to generate money, and carrying on the family name. The results showed that, among these factors, the relationship of family contribution, the ideology of being supported by sons, and carrying on the family name with male preference was significant. This study is among the first to explore the factors affecting male preference that could have resulted in China’s gender imbalance. The findings of this research are also important as references for the development of the population strategy and policy instruments used to manage the demographic problems in China.

This paper evaluated whether the citizens are satisfied with outcomes and performance of lockdown initiatives in defending against COVID-19. We statistical analyzed participants’ characteristics and used a logit regression to analyze the factors associated with their experience and satisfaction with the lockdown initiative. According to our results, the issues of information disclosure, reasonable resource arrangements, and timely governmental responses significantly influenced the experiences of citizens during the lockdown period. The findings can guide policy makers regarding implementing more progressive initiatives to limit the spread of COVID-19 and facilitate the use of emergency measures for the sake of public health.

This paper explores the initiation process of the long-term care insurance (LTCI) policy in China’s social security sector, and focuses on policy-oriented learning activities to develop initiatives from German lessons. It presents a case from the LTCI pilot program, which serves as a new policy product that provides care to the elderly and disabled and upgrades the social security sector’s performance. This study implements policy-oriented learning to construct an analytical framework and applies it to China’s social security system. This research suggests that policy-oriented learning is a rational tool used to manufacture policy products that enable intellectual development and can provide roadmaps for administrative reform. The findings contribute to the current knowledge on policy-oriented learning by offering new insights from China’s experience with LTCI, thus helping to fill the gaps that are created when policy-oriented learning is applied to different systems and contexts, with unique cultural, traditional, and political characteristics.

In 2017, Yongji County, which is located in Jilin Province, China, was devastated by its worst floods for generations. Consequently, the people of Yongji County suffered losses due to both the natural disaster and the deficiencies of disaster management. The aim of this research was to evaluate the factors that influenced the experiences of victims to provide insights into the performance of disaster management. Statistical analysis was employed to describe the functions and role of disaster management in the 2017 Yongji County flood. The Logistic regression also was adopted to explore the association between the performance and outcomes of disaster management experienced by victims, and gender, age, profession, frequency of disasters, the efficiency of defense measures, the efficiency of rescue, the loss of property, the degree of normal life and productivity recovery, the satisfaction of governmental compensation, the degree of disaster information disclosure, the government attitudes, the mechanism of accountability, and public safety education. This paper is among the first studies to identify the factors that affect victims’ perceptions in assessing the performance of disaster management hosted by local government. Hence, this research makes an important contribution in assisting policymakers and officers in local government to improve performance in dealing with natural and environmental disasters.