Chinese Journal of Population Resources and Environment最新文献

A detailed investigation of the nexus between economic growth and energy use is imperative for formulating sustainable development policies. In this study, we examine panel cointegration and causality relations among economic growth, energy use, capital stock, and labor in 30 Chinese provinces between 2000–2019. We conduct a comprehensive empirical analysis based on panel modeling and a neoclassical production function. The findings of the second-generation panel unit root and co-integration tests reveal that these variables have long-term co-integration linkages. We then perform a panel cointegration estimation using the fully modified ordinary least squares technique and find that total energy consumption, electricity consumption, capital stock, and labor significantly influence economic growth at the national and regional levels in China. Moreover, the outcomes of the Dumitrescu-Hurlin causality test indicate the existence of a two-way causal nexus between economic output and total energy consumption at the national level, but only a causal link from GDP to total energy use in the eastern and central regions. Conversely, a causality from total energy use to economic output is identified in the western region. Finally, we provide policy implications for the sustainable development of both energy and the economy at the national and regional levels.

Modeling urban land-use dynamics is critical for urban experts’ and infrastructure managers’ planning. This study attempts to explore the land-use/land-cover (LULC) dynamics of Gondar using satellite images from 1984 to 2020. Markov-Chain and Cellular Automata (MC-CA) models have been recognized as performing well in predicting urban land-use change. However, only a few models work in Ethiopia in general, and no study in Gondar has applied this approach to study urban land-use patterns. Therefore, Gondar land-use/land-cover changes of Gondar were predicted using the MC-CA model in IDRISI. The built-up area in Gondar city covered 1 413 ha (3% of the total area) in 1984 and increased to 2 380 ha (5%) in 1994; 21 153 ha (45.5%) in 2004; 22 622 ha (48.7%) in 2014; and 23 427 ha (50.5%) in 2020. The area has been predicted to reach 57.5% in the 2050s, showing a faster increase that will cause a very vast loss of farmland. This will increase urban sprawl challenges as well as overall environmental disequilibrium in the preceding decade. Thus, innovative and careful structures and systems in urban planning are required to secure a sustainable urban future and to make our cities livable and competitive in the paradigm of sustainable cities.

This study examines the effects of digital financial inclusion on non-farm employment of rural labor and the mediating mechanism of innovation and entrepreneurship activity using China Family Panel Studies (CFPS) and the provincial index of digital financial inclusion. Through the empirical test of the Probit model and mediation effect model, we found that: firstly, digital financial inclusion can promote non-farm employment of rural labor, with the level of digitalization having the most significant impact; secondly, by encouraging innovation and entrepreneurial activity, digital financial inclusion can promote non-farm employment of rural labor; thirdly, the driving effect of digital financial inclusion on non-farm employment of rural labor is more pronounced among the unmarried, eastern region, and male labor. Therefore, we should improve the construction of rural digital infrastructure and accelerate the development of inclusive rural finance to promote more diversified non-farm employment options for “disadvantaged groups”; encourage and support innovation at the government level, and create a favorable atmosphere for innovation and entrepreneurship. Simultaneously, farmers’ digital literacy and financial knowledge should be improved so that more can adopt and take advantage of digital financial inclusion.

This study uses carbon emission data at the provincial level in China between 1998–2018 and the proportion of the total import and export trade between provinces and the Association of Southeast Asian Nations (ASEAN) in GDP to measure the level of China-ASEAN trade openness. It examines the impact of China-ASEAN trade openness on carbon emissions and its transmission mechanism, and selects the RMB/USD exchange rate as an instrumental variable to address the endogeneity of China-ASEAN trade openness variables. The impact of China-ASEAN trade openness on China’s environment is estimated within a two-stage least squares framework. The results show that trade openness between China and ASEAN positively impacts China’s environment and can facilitate carbon emission reduction. The scale, structural, and technology effects brought by China-ASEAN trade liberalization jointly promote China’s carbon dioxide emission reduction. An inverted “U” relationship is found between economic growth and environmental quality in China, and some provinces and municipalities have now crossed the inflection point of the curve, in which carbon emi-ssions decrease with an increase in per capita wealth.

To achieve the goals of carbon peaking and carbon neutrality and maintain high-quality economic growth, China is currently striving to improve the quality of development of its power sector. In this regard, revealing the regional differences and evolutionary trends in the development quality of China’ power sector has a high value to inspire the next improvement direction toward how to integrate regional power recourses to an overall optimization level. Motived by this purpose, this paper uses the entropy method to evaluate the comprehensive and subsystem indices of the development quality of the power industry, and reveals their regional differences and evolutionary trends with the help of the Dagum Gini coefficient and Kernel density estimation methods. The findings show that: There are obvious regional differences in the development quality of China’s power industry, and the differences are steadily declining in all regions except the West. Regional differences are mainly derived from inter-regional differences, with the largest inter-regional differences in the East-Northeast region. Intra-regional differences show a distribution pattern of East > West > Northeast > Center.

The digital economy has become an important driver for stimulating economic growth. The digital economy has now widely penetrated the fields of economy and society, providing new opportunities for the development of urban-rural integration. Based on panel data for 30 provinces in China from 2011 to 2020, this study constructed an index system for the integration of the digital economy and the development of urban–rural areas and conducted a systematic measurement analysis. Additionally, we used a two-step system of GMM estimation to analyze the impact of the digital economy on the development of urban-rural integration. The findings demonstrate the significant imbalance paradox of China’s digital economy development, which is shown in a gradient where the eastern region is higher than the center and the central region is higher than the west. Urban-rural integration levels in China fluctuate and display geographical variance, typically displaying high levels in the east and low levels in the west. Urban-rural integration is significantly encouraged by the digital economy, yet it varies in variability between different areas and dimensions. Additionally, rural human capital moderates the favorable effects of the digital economy on urban-rural integration. As a result, in order to achieve the integrated development of urban and rural areas, it is imperative to fully exploit the active role of the digital economy, better support the development of rural revitalization, bridge the “digital divide” between urban and rural development, and build a strong foundation for the formation of a digital urban-rural integrated development pattern with urban and rural areas and common construction and sharing.

Electrical and electronic waste (e-waste) is a growing challenge, matching the widespread boom in the use of information and communication technology. Opposite to an alarming increasing amount of e-waste, a low rate of consumer engagement in ensuring the proper disposal of such materials intensifies the pressure on the existing e-waste crisis. To deal with this thorny problem, it is of great interest to grasp consumers’ disposal and recycling behavioral intentions. Therefore, this study attempts to understand complementary perspectives around consumers’ e-waste recycling intention based on the integration of the valence theory and the norm activation theory. Four data mining models using classification and prediction-based algorithms, namely Chi-squared automatic interaction detector (CHAID), Neural network, Discriminant analysis, and Quick, unbiased, efficient statistical tree (QUEST), were employed to analyze a set of the 398 data collected in Vietnam. The results revealed that the social support value is by far the most critical predictor, followed by the utilitarian value, task difficulty, and monetary risk. It is also noteworthy that the awareness of consequences, education background, the ascription of responsibility, and age were also ranked as critical affecting factors. The lowest influential predictors found in this study were income and gender. In addition, a comparison was made in terms of the classification performance of the four utilized data mining techniques. Based on several evaluation measurements (confusion matrix, accuracy, precision, recall, specificity, F-measure, ROC curve, and AUC), the aggregated results suggested that CHAID and Neural network performed the best. The findings of this research are expected to assist policymakers and future researchers in updating all information surrounding consumer behavioral intention-related topics focusing on e-waste. Furthermore, the adoption of data mining algorithms for prediction is another insight of this study, which may shed the light on data mining applications in such environmental studies in the future.

With the pace of global sustainable development, China has improved significantly in tackling environmental problems such as carbon emissions, climate change, air, water, and soil pollution, and wildlife extinction. Our study shows that despite China’s economic policy reform, several issues persist, including inequality between society and region, depletion and waste of resources, and damage to the natural environment. The study observed that China shuts low-level oil and coal-based power plants to prevent air pollution, promote a zero-carbon world, and reduce carbon intensity to 18.8%. The country also increased forest coverage by nearly 23.4%, declared five national parks in 2021, cleaned 98% of polluted water bodies, and improved the air quality in many big cities. A country like China has shown deep concern for environmental sustainability and has formulated many policies, laws, and regulations to prevent and conserve the environment and biodiversity and ensure sustainable economic development. This study argues that the Chinese concept of ecological civilization construction adheres to global sustainable development as both pursuits of achieving sustainable conservation of natural resources and improving the livelihoods of the people. Therefore, this paper reviews China’s policies toward ecological civilization (EC), which aim to create a beautiful China by 2035 on the outline of the UN Sustainable Development Goals 2030. The present study also addresses the issues the Chinese government faces while implementing environmental sustainability.

Based on three datasets of the Chinese Social Survey (CSS) 2013, 2015, and 2017 and the National Statistical Yearbook, this study examined whether and in what ways using the Internet may or may not affect the public evaluation of government environmental governance (GEG). There are three main findings. First, Internet use has a negative influence on the public evaluation of GEG. Second, there has been an urban-rural difference in terms of Internet use; especially for the rural resident, increasing their use of the Internet significantly lowered their evaluation of GEG. Third, Internet use affects GEG mainly through political trust, whilst it tends to enhance people’s perception of environmental problems; however, it has little influence on their evaluation of GEG. This finding implies that public evaluation of GEG should be viewed as an important inter-subjective dimension of GEG; especially in the Internet era, it has become increasingly necessary for the government to not only continuously improve the quality of governance by dealing with actual/practical environmental issues, but also enhance its ability to react to the public opinions online effectively and appropriately.