The global greenhouse effect caused by excessive energy CO2 emissions has seriously affected the sustainable development of the society, and energy consumption and production mainly come from industrial system and energy system. This paper used the structural decomposition analysis (SDA) and the input-output analysis to study the structural emission reduction of China's industrial and energy systems in 2007-2015.The results showed that: (1) From the analysis of structural factors, the final demand effect was the main factor to promote the growth of energy CO2 emissions, and the energy intensity effect played a weak role in promoting the growth of energy CO2 emissions. (2) From the perspective of energy systems, the emission reduction effect of blast furnace gas, raw coal, refinery dry gas and natural gas is obvious, while that of crude oil, gasoline, fuel oil and kerosene is not obvious. (3) From the perspective of China's industrial systems, the tertiary industry played a major role in the final demand effect, followed by secondary industries and the primary industry in turn. Finally, this paper provided a theoretical basis and realistic guiding route for the accurate and efficient emissions reduction of energy system and China's industrial system.
The establishment of a carbon trading market is crucial for China to fulfil its carbon emission commitments through a market mechanism. As a market-based environmental regulation instrument, Emission Trading Scheme (ETS) has been attracted increasing attention worldwide, while the effect of ETS on low-carbon economy efficiency (LEE) has not been fully investigated, thus inspiring us to fulfil this research gap. Using the panel data of China’s 283 selected prefecture-level cities during 2006–2017, we adopted the difference-in-differences (DID) model, propensity-score-matched DID (PSM-DID) model, and the spatial DID model to model the direct and indirect effects of China’s ETS on LEE at national, regional, and local (resource-based cities with different development stages) levels. The robust results yield that ETS directly and significantly improved China’s LEE at the national level. Still, the LEE in ETS pilot region will increase by approximately 4.3% compared with untreated cities, while the spatial heterogeneity of this effect is captured at regional and local levels, which emphasises the necessity of a completed market construction and classified supervision. The results of this paper provide important insights for strengthening the policy design of a nationwide carbon market, and a reference point for other regions and countries, especially developing countries, in refining a carbon trading market.
The Chinese central government established eight pilot zones in five provinces for green finance reform and innovations (GFRI) in 2017. The pilot zones promote green finance development and explore the propagable and reproducible experiences regarding mechanisms and institutions. Adopting a sample of China’s listed companies from 2012 to 2021, this paper constructed a quasi-natural experiment and investigated the GFRI policy’s effect on firms’ total factor productivity (TFP) using the difference-in-differences (DID) method to verify the implementation effect of the GFRI policy. Furthermore, heterogeneity analysis and mechanism analysis were conducted to identify the guidance effect and deep mechanisms of the GFRI policy. The empirical results demonstrated that firms’ TFP in pilot zones increased substantially after implementing the GFRI pilot policy, confirming that the policy had a strong incentive effect. The corresponding promoting effect was particularly significant for non-state-owned companies, the eastern and central regions, and firms in the growth stage. Further mechanism analysis revealed that the GFRI pilot policy can stimulated firms’ TFP by promoting technological innovation and improving resource allocation efficiency. This paper’s empirical findings are essential in improving relevant policies and expanding the pilot zones.
As language evolves and changes one gradually discovers the differences and characteristics of its acquisition in both genders. When it comes to second language learning, a number of internal and external factors are responsible for its impact. This paper examines gender differences in second language acquisition by looking at psychological factors and motivations, including personality, self-esteem, tension, internal motivation and the brain structure of learning, as well as the multiple ways in which learning occurs and the stereotypes that exist in society. Based on an extensive literature review and findings from a wide range of scholars, this paper concludes that there are multiple reasons for gender differences in second language learning ability. Individual personality and physiological functioning can have varying degrees of influence. Differences in learning ability can also arise when guided by different learning styles. In addition, existing social prejudices and stereotypes, as well as the home environment, may also contribute to gender differences in second language learning.
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