Despite the extensive attention paid to emissions trading scheme (ETS) approaches, few studies have examined whether such ETS policies can lead to sustainable development in China. Drawing on the ideas of coupling and synergistic development, this study views sustainable development as the result of the interactions between the economy and the environment and constructs an index system to measure economic development and environmental quality. The system coupling model is used to reflect the synergistic interactions between the economy and the environment systems. The coordination degree model is then used to assess the economic–environmental coupling coordination degree in order to measure sustainable development. The empirical results show that the ETS can help in achieving economic–environmental sustainable development in the pilot cities. Moreover, the better the socioeconomic development of a city, the better effects of the ETS on sustainable development. However, it is more difficult to achieve economic–environmental coordinated development in industrially developed areas (e.g., Guangdong). These findings provide empirical evidence that the market-based ETS could alleviate the conflict between economic development and environmental pollution and could help in achieving sustainable development in emerging economies.
Background
With the rapid growth of the ageing population, the operating burden of China’s basic medical insurance fund is becoming increasingly heavy. To counter rapid population ageing and ameliorate a series of problems, China has adjusted its fertility policies several times. On January 1, 2016, the universal two-child policy was implemented. This study analysed the impacts of the adjustment to the fertility policy and potential improvements in fertility intention on the insured population and medical insurance fund sustainability.
Methods
We used an actuarial science method and took the urban and rural residents’ basic medical insurance (URRBMI) of China, which covers most urban and rural residents, as an example to build a dynamic forecast model of population growth and a dynamic actuarial model of medical insurance funds.
Results
Compared with the original policy, under the current fertility intention (40%) with the universal two-child policy, the ageing of the population structure of URRBMI participants will decline significantly after 2026, and individuals aged 65 and over will account for only 19.01% of the total participants in 2050. The occurrence of the current deficit and accumulated deficit of the URRBMI fund will be postponed for one year to 2022 and 2028, respectively. If fertility intentions continue to rise, the ageing degree of the population structure will decrease, and the deficit would be further delayed.
Conclusions
The universal two-child policy is conducive to improving the degree of overall population ageing, delaying the occurrence of a URRBMI fund deficit, and improving the sustainability of URRBMI funds. If fertility intention increases, the effects would be stronger. However, since the adjustment of the universal two-child policy has a certain time lag, it will take time to demonstrate this impact. Therefore, while actively promoting the universal two-child policy, other measures should be taken, such as improving the fertility desire among couples of childbearing age and reforming medical insurance payment methods.
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