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The research calculated the waste paper recovery rate, and analyzed the main factors influencing waste paper recovery rate in China with time series data from 1970 to 2012. The consequent recovery rate and utilization rate of waste paper show that the recovery of paper products has been experiencing a rapid growth in China, but it cannot meet the domestic need. The empirical analysis proves that demand is the main driver to stimulate the increase of waste paper recovery rate in China; the increased average GDP per capita and proportion of waste paper pulp are two other important factors; the increased urbanization rate does not exert significant influence. In the circumstance of insufficient timber supply, the policy of eliminating straw pulp capacities for paper-making indusrty improves the recovery rate of waste paper. [ABSTRACT FROM AUTHOR]

Several research efforts were dedicated to analysing the effects of foreign direct investment (FDI) inflows on gross domestic product (GDP) and employment in the host economies. The variations in the conclusions signal that other variables influence and moderate the effects of FDI on GDP and employment. Institutional elements receive limited research attention, despite their influence on the host economies. This paper investigates the moderating role of institutional elements in the FDI-host economies on FDI’s effects on GDP and employment with China and India as case studies. The approach utilises three principal methodologies. The first methodology presents an in-depth analysis of China and India, highlighting selected institutional elements with the potential to influence FDI’s effects. The second methodology confirms the presence of a positive correlation between FDI and GDP and a negative correlation between FDI and employment-to-population ratio (EPR) in both China and India. The FDI, GDP purchasing power parity per capita, and EPR datasets are extracted from the World Bank – DataBank World Development Indicators to ensure the consistency of the data. The results of the quantitative analysis validate the qualitative analysis. The qualitative analysis confirms the moderating role of the selected institutional elements with variations in direction and strength. Significant variations in FDI’s effects on GDP and employment are strongly related to variations in the institutions of governance. The institutions of governance include the functionality of the state organs, the efficiency of the legal system and enforcement of the rule of law, and the quality of implementation of FDI-supportive policies. The findings aim to increase the absorption of the positive effects of FDI on GDP and employment in the respective countries. The research is a cornerstone of in-depth future research into the following areas: the role of selective FDI and constructive conditional FDI policies, the functionality of judicial authority controls, and FDI favourable exchange rates and interest rates policies. The novelty and contribution of the paper lie in its comprehensive exploration of the moderating role of institutional elements on the effects of FDI on GDP and employment in host economies, with a specific focus on China and India. The paper contributes significantly to the academic literature on FDI and economic development by emphasising the importance of institutional factors and providing actionable insights for policymakers and researchers. [ABSTRACT FROM AUTHOR]

High-energy consumption and high-emission industries contribute a lot to economic development, but their carbon emissions are also huge. In order to achieve the dual-carbon target as early as possible, it is necessary to reduce the carbon emissions of high-energy consumption and high-emission industries. This paper selected five representative factors (population, per capita gross domestic product (GDP), energy intensity, energy structure and carbon emission coefficient) and adopted the logarithmic mean divisia index (LMDI) method to decompose the driving factors of carbon emissions. Therefore, this paper uses Tapio decoupling model to analyze the decoupling relationship between the two factors with the greatest impact on carbon emissions and carbon emissions. The results show that: (i) There is a good decoupling between high-energy consumption and high-emission industries and per capita GDP, and the impact of per capita GDP on carbon emissions will gradually decrease in the future; (ii) The decoupling relationship between carbon emissions and energy intensity is poor. For some industries, the reduction of energy intensity can help reduce carbon emissions. Finally, this paper puts forward some suggestions to promote carbon emission reduction. This paper provides theoretical support for studying how to reduce carbon emissions and formulate relevant emission reduction policies in the high-energy consumption and high-emission industries. [ABSTRACT FROM AUTHOR]

Urban underground space (UUS) development has been acknowledged as a positive contribution to urban resilience (UR). Such contribution has been qualitatively addressed in recent years, but only quantitatively discussed in few studies. Quantitative evaluation methods for UR are widely used in China and around the world, but the role of underground space is barely included. This paper provides a way to bridge this gap on the city scale. A UR evaluation framework was carefully constructed that covers the basic aspects and elements of UR. The contributions of UUS to UR were identified and integrated into the UR evaluation framework, and the measurement methods for each indicator related to UUS were determined. A case study of 19 sample cities in China were conducted using the integrated evaluation model. Correlation analysis and clustering analysis were further adopted to interpret the evaluation results, mainly with three indicators reflecting the level of UUS development, namely UUS area (m²), UUS density (104 m² /km² ) and UUS area per capita (m² / person). The results showed a strong correlation between UUS area and UR. The average proportion of UR provided by UUS in the 19 sample cities was 16.46%, while the maximum figure reached 29.20%. The sample cities were clustered into four categories based on the relationship between the proportion of UR provided by UUS, UUS area, and GDP per capita, where both high and low UUS area tend to provide less proportion of resilience than the medium UUS area. Corresponding suggestions for UUS utilization were proposed to assist cities in achieving urban resilience. [ABSTRACT FROM AUTHOR]

The article reports on the result of the survey by the Research and Markets in Dublin, Ireland regarding the increasing percentage rates of paper production in China in 2004. Accordingly, the papermaking industry in China shows development in 2004 with 49.5 million metric tons paperboard production which is 15.1 percent more than in 2003. China's gross domestic product in 2004 reached to 9.5 percent much higher than its 7 percent target.

China is transitioning its industrial structure from labor-and resource-intensive industries that previously contributed significantly to the country's GDP growth to technology-intensive industries emphasizing a highly-skilled workforce and sustainability to achieve high-quality economic growth. This paper examines the impact of the RMB exchange rate on high-quality economic growth through theoretical modeling and empirical analysis and discusses the variable of overseas education to explore the mechanism of how the RMB exchange rate and overseas education jointly impact high-quality economic growth. The research sample includes the National Bureau of Statistics data on education from 1995 to 2015, the Bank for International Settlements (BIS) data on the RMB exchange rate, and the added value of China's high-quality economic growth estimated based on the national economy data. An empirical analysis of theoretical expectations was conducted, finding that RMB appreciation could make a positive contribution to China's high-quality economic growth; RMB exchange rate fluctuations would impact the relative cost of overseas education and overseas returnees could have a positive impact on domestic resource utilization efficiency and domestic capacity to make sci-tech innovations, thereby injecting vitality to high-quality economic growth. This study focuses on both the RMB exchange rate and the population studying abroad, providing additional observation dimensions to existing research. [ABSTRACT FROM AUTHOR]

Existing macroeconomic forecasting methods primarily focus on the characteristics of economic data, but they overlook the energy-related features concealed behind these economic characteristics, which may lead to inaccurate GDP predictions. Therefore, this paper meticulously analyzes the relationship between energy big data and economic data indicators, explores the coupling feature mining of energy big data and economic data, and constructs features coupling economic and energy data. Targeting the nonlinear variation coupling features in China's quarterly GDP data and using the long short-term memory (LSTM) neural network model based on deep learning, we employ wavelet analysis technology (WA) to decompose selected macroeconomic variables and construct a prediction model combining LSTM and WA, which is further compared with multiple benchmark models. The research findings show that, in terms of quarterly GDP data prediction, the combined deep learning model and wavelet analysis significantly outperform other methods. When processing structurally complex, nonlinear, and multi-variable data, the LSTM and WA combined prediction model demonstrate better generalization capabilities, with its prediction accuracy generally surpassing other benchmark models. [ABSTRACT FROM AUTHOR]

Background We previously showed that the number of publications in dermatology is increasing year by year, and positively correlates with improved economic conditions in mainland China, a still developing Asian country. However, the characteristics of publications in dermatology departments in more developed Asian countries such as Japan and South Korea are unknown. Methods In the present study, publications from 2003 through 2012 in dermatology in Japan, South Korea and mainland China were characterized. All data were obtained from www.pubmed.com. Results Dermatology departments in Japan published 4,094 papers, while mainland China and South Korea published 1528 and 1,758 articles, respectively. 48% of articles from dermatology in Japan were original research and 36% were case reports; The number of publications in Japan remained stable over time, but the overall impact factors per paper increased linearly over the last 10 year period (p < 0.05). In mainland China, 67% of articles from dermatology were original research, while 19% were case reports; The number of publications and their impact factors per paper increased markedly. In South Korea, 65% of articles from dermatology were original research and 20% were case reports. The impact factors per paper remained unchanged, despite of the fact that the number of publications increased over the last 10 year period (r2 = 0.6820, p = 0.0032). Only mainland China showed a positive correlation of the number of publications with gross domestic product per capita during this study period. Conclusions These results suggest that the total number of publications in dermatology correlates with economic conditions only in developing country, but not in more developed countries in Asia. The extent of economic development could determine both the publication quantity and quality. [ABSTRACT FROM AUTHOR]

Constraints and incentives of the ecological policy have an important impact on the coordinated development of ecological areas. Based on the panel data of 1613 counties in 23 provinces in China from 2002 to 2019, this paper analyzes the impact of this policy on economic development using the quasi-natural experiment of the transfer payment in national key ecological functional areas (TPNKEFA) and studies the impact of the transfer payment scale on economic development based on the panel threshold model. First, the results reveal that the TPNKEFA can significantly boost economic development, compared with the control group, TPNKEFA can increase gross domestic product (GDP) and per capita GDP by 6.14% and 10.72%, the results have been validated by some placebo tests, and the impact of this policy on economic development is sustained and effective. Second, heterogeneity results show that TPNKEFA has the greatest positive effect on the economic development in the eastern region, followed by the central region, and the least positive effect on the western region. Furthermore, the TPNKEFA facilitates local economic development primarily by increasing human capital in ecological functional areas. Third, the capital scale of TPNKEFA has the double-threshold effect on economic development, the larger the scale is, the stronger the effect is. The capital size of TPNKEFA has the greatest impact on regional economic growth in eastern region, whereas it has the weakest impact in western region. [ABSTRACT FROM AUTHOR]

This paper applies a structural decomposition of the input-output tables to investigate the sources of changes in the GDP of China, paying special attention to the import substitution of intermediate inputs. It is argued that the specific way GDP is decomposed in this paper sheds more light on the origin of growth than does the conventional decomposition of GDP by its final demand components. The results of the decomposition show that import substitution of intermediate products, which is an act of de-globalization of trade and a model of industrialization some Asian newly industrializing economies followed decades earlier, also became important in China, but only belatedly: in 2011–2012 and 2013–2014. The phenomenon is found to be significant in the manufacture of (i) computer, electronic and optical products, (ii) chemicals and chemical products, (iii) coke and refined petroleum products, and (iv) basic metals. [ABSTRACT FROM AUTHOR]

China's local government debt (LGD) has recently become the focus of economic policy debates. However, information about LGD and its impact on economic growth in the Chinese economy is scarce. This paper attempts to present an empirical investigation of the impact of China's LGD on economic growth. It is probably the first of its kind to focus on China and thus contributes to the general literature on the relationship between government debt and economic growth. The paper first provides an assessment of LGD in China's regional economies, using recently released auditing statistics and other available secondary information. It then applies conventional growth analysis methods to examine the impact of LGD on regional growth in China. Various scenario and sensitivity analyses are also conducted, to accommodate the inadequacy and potentially poor quality of debt statistics. [ABSTRACT FROM AUTHOR]

The current study was to investigate the quantity and quality of researches in the field of ankylosing spondylitis, and to reveal the characteristics of worldwide productivity on this disease. This was a bibliometric study on ankylosing spondylitis using Web of Science. The numbers of papers, citations, research output normalized by population and gross domestic product, and the main active countries were analyzed. A total number of 7239 papers were published between 2008 and 2017. The yearly number of papers published during this period showed a significant increase (p < 0.001). North America, West Europe and East Asia were the main regions for AS papers. High-income countries contributed the greatest proportion of papers (70.49%). The research productivity from middle- and low-income countries was low (29.45%; 0.06%). The United States was the country with the greatest contributions between 2008 and 2017 (12.47%), followed by China (12.17%), Turkey (8.34%), Germany (7.82%), and the United Kingdom (5.97%). Significantly positive correlations were proved between the number of papers and population/gross domestic product (p < 0.05). From 2013, the number of AS publications by the authors from China exceeded those from the United States. However, China had far less total citations (7219 vs. 22,043) and average citations (8.19 vs. 24.41) than the United States. Denmark had the greatest productivity when normalized by population, followed by Norway, and Netherlands. When normalized by gross domestic product, Denmark led the top list, followed by Netherlands, and Greece. Papers from Australia showed the highest average citation (32.64), followed by Netherlands (31.63), and Germany (26.88). The current study showed a noticeable growth in global research output on ankylosing spondylitis between 2008 and 2017. High-income countries especially the United States had the greatest contributions. The contributions from middle- and low-income countries were considerably small. The number of papers published by countries was positively associated with their population and gross domestic product. Although China had exceeded the United States in the quantity of yearly AS publications, the quality of papers from China was lower compared to the United States. European countries may have better performance relative to their population and economic size. [ABSTRACT FROM AUTHOR]

Financial inclusion refers to a process that ensures the ease of access, availability, and usage of the financial system for all members of an economy. This paper aims to study financial inclusion's impact on enterprise innovation and compare the different effects of traditional and digital financial inclusion. Existing papers mainly focus on digital financial inclusion's influence. Based on China's data, this paper fills the gap by constructing an index system to measure traditional financial inclusion and discussing the impact mechanism of the two kinds of financial inclusion on enterprise innovation (output and efficiency). The results illustrate that traditional financial inclusion inhibits the innovation output of enterprises, while digital financial inclusion has a positive effect. However, both traditional and digital financial inclusion is still in the stage of constraining the innovation efficiency of enterprises. Moreover, the two types of financial inclusion function differently for enterprises of different sizes and ownership. Evidence from China is expected to reveal the features of this relationship and inspire research in more economies. [ABSTRACT FROM AUTHOR]

Energy efficiency is the key to green development, and the government plays a vital role in energy efficiency. This paper clarifies the mechanism by which the Yangtze River Delta Economic Coordination Committee affects the energy efficiency of urban agglomeration by promoting market integration. Based on panel data of China's prefecture-level cities from 2004 to 2017, we take the Yangtze River Delta Economic Coordination Committee as a quasi-natural experiment of government cooperation and use the difference-in-difference method to test whether this organization has enhanced the energy efficiency of urban agglomeration. The results show that the Yangtze River Delta Economic Coordination Committee can significantly improve energy efficiency in urban agglomerations. The mechanism analysis shows that it reduces the energy consumption per unit of gross domestic product by enhancing the marketization level, perfecting the relationship between the government and the market, and improving the factor market development. The heterogeneity analysis shows that cities with lower city size, lower level of innovation, and cleaner industrial structures gain more benefits in energy efficiency from government cooperation in urban agglomeration. This paper provides empirical evidence for cities to realize integrated energy conservation through government cooperation and market integration. [ABSTRACT FROM AUTHOR]

Ternary interval number includes the total GDP amount in a certain period and its change range. Comprehensive information is more conducive to management decision-making. Affected by regional characteristics and national macro-control, the development trend of GDP in various regions of China in the past 15 years has been different. Some central regions grew rapidly in the early stage and fell back in the later stage, showing a saturated growth trend. Some coastal economically developed areas showed exponential growth. While some regions show an unstable upward and downward fluctuation trend. In order to predict the development trend of different GDPs, a matrix model based on exponential and polynomial regression, which can directly model the ternary interval number, is proposed in this paper. In order to eliminate the random fluctuation of data, the original ternary interval number sequence is accumulated based on the data preprocessing method in the grey model, which makes the general non-negative sequence show quasi-exponential growth so that it can be applied to the exponential-polynomial matrix model. The particle swarm optimization algorithm and the least square method are combined to estimate the parameters of the new model. The new model, quadratic polynomial, GM (1, 1), and exponential function are used to predict the GDP of 31 regions in China from 2005 to 2020. The results show that the effect of the new model is better than other models in predicting GDP for 20 regions. [ABSTRACT FROM AUTHOR]

In the grey prediction, the GM(1, 1) model is an important type, but it sometimes shows big prediction errors. To improve the prediction precision of GM(1, 1) model, the paper makes improvements from the following three aspects: (1) to improve the data's adaptability to the model, the paper transforms the accumulated generating sequence of original time sequence; (2) to make the model meet the variation characteristics of data, the paper extends the grey action of traditional GM(1, 1) model; (3) to avoid big average simulation or prediction relative error of model, the paper considers the minimum of the maximum of the two errors as the optimization objective function. The new extended grey model is called the GM(1, 1, exp × sin, exp × cos) model. The paper uses an improved particle swarm optimization (PSO) algorithm for the parameter optimization of GM(1, 1, exp × sin, exp × cos) model and thus improves the model's convergence rate and precision. According to the model and method proposed, the paper builds a GM(1, 1, exp × sin, exp × cos) model for China's GDP per capita. Results show that the model has high precision. [ABSTRACT FROM AUTHOR]

This paper explores the impact of the political hierarchies of cities in China from different perspectives. First, we examine the economic disparities between prefectural cities and municipalities. Furthermore, this paper draws upon a quasi‐ experiment to analyze the impact of upgrading Chongqing to a municipality in 1997 using the synthetic control method. The city‐upgrading policy significantly increased Chongqing's gross domestic product (GDP) in the following 4 years. Finally, we find that the policy increased GDP in treated cities within 1200 km of Chongqing by about 10%–13% relative to the control cities. [ABSTRACT FROM AUTHOR]

China has established and assigned target responsibilities for local officials in energy conservation and created an evaluation indicator, which is a key institutional arrangement that provides local officials with political incentives to promote carbon abatement policies. In this paper, we elaborate on the relationship between China's target responsibility system and CO2 emissions using interprovincial panel data, grouping provinces into Eastern, Central and Western regions to compare China's CO2 emissions convergence between the periods of the 10th Five-year Plan and the 11th Five-year Plan. The analysis indicates that the target responsibility system does not noticeably change local officials' political incentives to engage in carbon abatement because the effect of the target responsibility system for energy conservation seems to be overshadowed by and subject to gross domestic product (GDP) growth targets. Against the backdrop of growing international pressure on climate change issues, this paper argues that China must include in the target responsibility system an indicator of absolute CO2 emissions reduction as a policy objective. [ABSTRACT FROM AUTHOR]

Background: The progress of green credit in China is accelerating, but its development is uneven and insufficient in different regions. And whether the issuance of green credit can effectively promote the improvement of the environment and economy is not well understood. Objective: Previous research has found that green credit promotes economic growth through improvement of the industrial structure and green technological innovation. However, these studies have not considered the positive externality of environmental improvement even though environmental improvement and economic growth are requirements of the sustainable development concept. Methods: We use the chain-mediated model to estimate the impact of green credit issuance on the economic growth of different provinces since the large-scale implementation of green credit in China with data from 2008 to 2016. Results and conclusion: This paper shows that the issuance of green credit can improve labor supply rather than labor productivity through the improvement of air quality to achieve regional economic growth. Such a chain-mediated path is different from the economic growth caused by industrial structural adjustment and green technology innovation. At the national level, every 1% increase in green credit issuance relative to industrial loans will increase the per capita gross domestic product (GDP) by approximately 4.6 yuan, or 0.012%, through air quality and labor supply, accounting for 2.875% of the total effect. Heterogeneity analysis indicates that due to regional industrial structure differences and diminishing marginal effects, the impact of green credit is stronger in the western region than in the eastern and central regions. For every 1% increase in the proportion of green credit issuance relative to industrial loans, the per capita GDP growth achieved through the chain-mediated path is approximately 30.17 yuan in the western region, approximately 6.6 times greater than that at the national level. Within a 95% confidence interval of 5000 bootstrap samples, this path is found to be true, and the chain-mediated effect accounts for approximately 12.96% of the total indirect effect. Limitations: The limitation of this paper is the measurement of green credit. Although green credit has a large volume, it remains underdeveloped, and there is a lack of perfect indicators. Most existing studies have adopted only alternative or reverse indicators to measure the issuance of green credit. For example, this paper takes the interest expenditure of six high-energy-consuming enterprises as the reverse indicator, which may to a certain extent lead to the overestimation of the issuance of green credit and its impact on the environment and economy. Future research can accurately explore the performance of green credit on the basis of its mature development. [ABSTRACT FROM AUTHOR]

China joined the Paris Agreement, and the global 2°C and 1.5°C warming targets will be supported by China. In order to achieve these targets, China's CO2 emissions need to be cut deeply by 2050. The present paper presents studies from the integrated policy assessment model for China (IPAC) team about the impact on China's economic development of deep cuts in greenhouse gas (GHG) emissions, in order to realize the Paris climate change targets. With the requirement of deep cuts in GHG emissions in China, China's economic development will also be impacted in moving toward a low‐carbon or zero‐carbon emission‐based economy by 2050. This means the Chinese economy needs a strong transition over the next three decades, a relatively short time. All sectors in the economy need to seek ways to reduce GHG emissions, and this could change activities, industry processes and technologies in order to make the deep cuts in GHG emissions happen. This is the meaning of the economic transition toward to a low‐carbon economy. The findings of the present paper include: a significant transition in the energy supply sector; a high rate of electrification in all end‐use sectors; and a technology transition in the transport sector. Transitions will also occur in the traditional industrial sectors, including steel making, cement manufacture, and the chemical sector. The availability of low‐cost renewable energy could change the allocation of industries, which could potentially have a strong impact on regional economic development. Deep cuts in CO2 emissions in China need not be a burden for economic development, as the IPAC results show there will be a more than 1.5% increase of gross domestic product by 2050 in the deep cut scenario compared with the baseline scenario. [ABSTRACT FROM AUTHOR]

Background China has been experiencing huge changes in all aspects, including dermatologic research, since its reform in 1978. However, it is not known how the economic and intellectual development has influenced the publication trends in the field of dermatology, which could mirror the scientific development in other medical disciplines. In the present study, we analyzed publication trends from dermatology departments in mainland China from 2002 to 2011. Methods All publication data were obtained from . Only papers published from dermatology departments in mainland China were used for analysis. Results The number of publications increased 10-fold over this 10-year period. A total of 1231 articles were published in English in 251 journals between 2002 and 2011. A total of 129 journals published only one paper from dermatology departments in mainland China. Over 60% of articles were original research, and 21.7% were case reports. Among these 251 journals, foremost was the Journal of Clinical Experimental Dermatology, which published 5.9% of all papers from mainland China; 2.7% of papers were published in the Journal of Investigative Dermatology. The number of publications positively correlated with the changes in gross domestic product per capita during the study period. Conclusions These results suggest that the number of publications in the dermatology field has increased markedly in mainland China over the last 10 years. This dramatic increase in publications could be attributed, at least partially, to the significant improvement in economic conditions in mainland China. [ABSTRACT FROM AUTHOR]

Demand and supply still remain the main instruments in determining the role of Information and Communication Technology (ICT) in gross domestic product growth. There is an increasing body of research, investigating the determinants of economic growth in China. Most studies have focused on technology, which has resulted in increased demand for new products and services. This demand on the supply side naturally accounts for the increase in efficiency in production of services, goods and infrastructure. The market forces of demand and supply depend on: knowledge spillovers, triadic patents, and people employed in the high-tech sectors. Although increases in innovation stemming from R&D activities are palpable, the extent of economic growth is contingent on the market size (IMF, 2004). This paper investigates the relationship between exogenously-determined growth, proxied by ICT imports, and endogenous drivers of economic growth, by employing ICT exports. The paper verifies the hypothesis by employing a machine learning approach to Pearson's correlation and employs the Augmented Dickey- Fuller test to test for multicollinearity. The study postulates evidence-based policy recommendations that facilitate transition of the Chinese economy towards innovation-driven and consumer-led economy. [ABSTRACT FROM AUTHOR]

China, known as the largest carbon emitter and the second largest economy worldwide, has continued to put effort into the understandings of the main drivers of carbon emission and their decoupling statuses from its economic growth. Considering the significant differences of natural and social environments in different regions of China, this paper presents a regional-scale decomposition of energy-related carbon emission and its decoupling from economic growth by using the Logarithmic Mean Divisia Index (LMDI) and the Tapio decoupling method. The decoupling results indicate that carbon emissions in all regions show a stable decoupling trend from their economic development, which means that China is now on the right road for achieving a low-carbon economy. However, the decoupling status by the end of 2016 also indicates that most of the regions are still in the states of expansive coupling or weak decoupling, especially in Northwest (NW), which implies that the speed of decarbonization process is still not high enough. The decomposition results show that in all regions except NW, GDP per capita is the most influential factor leading to increasing carbon emissions, while energy intensity is the largest factor in reducing carbon emissions. In NW, both GDP per capita and energy intensity drive the increase in carbon emissions. The results in this paper could benefit China's regional policy-making and national strategies. [ABSTRACT FROM AUTHOR]

The International Monetary Fund (IMF) forecasts a gradual slowdown in the, otherwise strong, growth of the Chinese economy in the first half of the 2020s, and the anemic growth of the Western economies: the US and, especially, the EU27. Given the practical (and symbolic) importance of reaching 'the number one economy' status, the primary objective of the paper is to estimate the GDP (and the GDP PPP) of the observed economies over the next decade. The main contribution and finding of this paper is the estimation of future GDP trends for the US, China and the EU27 in the period 2025-30, based on the previous trends and the IMF 2020-24 projections. China's economy will become globally leading in 2029-2030. The basic research hypothesis is proven, given the fact that a change in the global economic position implies significant geopolitical consequences. Namely, while the US will almost certainly remain the leading global power in the 2020s, with the EU still continuing to focus on itself, China's economic growth will have rising global consequences, fueling the move towards the dispersion of authority. This conclusion is in line with the claims of the majority of the relevant authors who emphasize the increasingly limited possibility of the US unilateral actions. [ABSTRACT FROM AUTHOR]

In the context of the new normal, the global economy is entering a deep adjustment period, and the driving forces of development are also constantly changing. As a result, China's economy has also entered a "new normal" phase in which it is growing in a manageable and relatively balanced manner. In addition, the new normal characteristics of the power industry's development in China are also very significant, and they affect the adaptability of traditional power forecasting methods. By analyzing the new characteristics of China's economic development and the changing electricity demand in recent years, this paper quantitatively studied the effect of the national economy on the consumption of electricity. Meanwhile, a modified logistic model based on the change of the gross domestic product (GDP) growth rate is constructed to make a reasonable prediction of the future power consumption in China. Subsequently, by calculating the elasticity of electricity consumption in the future, it is found that the coefficient decreases each year, which indicates that electricity consumption in China is following a new trend. Based on the research results, this paper proposes rational suggestions for China's power development, and they are expected to provide references for the power planning and power industry layout in China. [ABSTRACT FROM AUTHOR]

The reliability of China's GDP data has been questioned for a long time. Prior studies have discussed the causes of GDP distortion in China, but the evidence on the economic consequences is scant. This paper examines the economic consequences of regional GDP distortion from the perspective of analyst forecasts. We find that regional GDP distortion leads to lower analyst forecast accuracy, and this result is robust to potential endogeneity. Further investigations show that analysts with information advantages have the ability to resist the distorted GDP data and issue accurate forecasts. Political pressure is another factor leading to inaccurate analyst forecasts. Our paper contributes to the literature by highlighting the importance of the reliability of GDP figures as a determinant of analyst forecast accuracy. [ABSTRACT FROM AUTHOR]

Water, energy, and food (WEF) are vital strategic resources for human survival and development, which are interacting positively or negatively. While WEF sustainability has received significant attention and extensive research has examined its interactions, there are a few studies exploring the trade-offs arising from advancing the sustainable development process. This paper aims to study the internal interrelation and external impact on WEF sustainability from the perspective of Sustainable Development Goals (SDGs). We first quantified the WEF sustainability at the provincial level in China from 2003 to 2020, then used panel vector autoregression (PVAR) to identify the interactions within the WEF system and examined how related SDGs actions (SDG 8, 12, 13) affected it. The findings revealed spatial disparities in sustainable processes across provinces. Internally, prioritizing water-sustainable actions fostered overall synergistic development, while trade-offs emerged between food and energy systems. Externally, SDG 8, 12, and 13 acceleration actions mainly contributed to WEF sustainability, but maintaining GDP growth and reducing CO2 emissions both presented challenges to sustainability. This study not only enriches the understanding of WEF sustainability from the SDGs perspective, but also provides valuable insights into how sustainable development actions can affect the WEF system. [ABSTRACT FROM AUTHOR]

Objective: Using pooled data from the 2010, 2012, and 2014 China Family Panel Studies, this paper elucidates the internal heterogeneity among non‐arranged marriages by examining changing patterns and determinants of mate selection in China from 1950 to 2014. Background: Previous research has documented a decline in arranged marriages and a rise in self‐initiated marriages in the Asian context. Methods: This study uses two measures to capture the nuanced nature of mate selection, namely, arranged versus non‐arranged marriages among all couples, and introduced versus self‐initiated marriages among non‐arranged couples. Results: While arranged marriages declined rapidly and were replaced mostly by introduced marriages before 1980, after 1980, self‐initiated marriages began to increase. Urbanization and better education led to more non‐arranged marriages, particularly through self‐initiated means. The influence of county‐level per capita GDP on mate selection is quadratic. Conclusion: The two‐stage transitions in mate selection reflect the importance of accounting for both structural and ideational factors in explaining these changes. Implications: We challenge the assumed unilinear change from arranged marriages to self‐initiated marriages along the processes of economic development. The intensified economic pressures may have driven some young adults back to introduced, even arranged, marriages. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to find the impact of the trade war between the USA and China on Asian economies. Apart from macroeconomic variables associated with trade, this study explicitly creates a trade war scenario and trade war participant dummies. Using the neural network multilayer perceptron, this study checks for the causal linkages between the predictors and target output for the panel of Asian economies and the USA. Design/methodology/approach: A conceptual model of the after effects of trade war in a quadrant is developed. Variables related to trade and tariffs are included in the study for a panel of 19 Asian economies. The feedforward structure of neural network analysis is used to identify strong and weak predictors of trade war. Findings: The hidden layers of the multilayer perceptron reveal the inconsistency in linkages for the predictors' services exports, tariff measures, anti-dumping measures, trade war scenario dummy with gross domestic product. The findings suggest that to curtail the impact of the trade war on Asian economies, predictors with neural evidence must be paid due weightage in policy determination and trade agreements. Originality/value: The study applies a novel and little explored AI/ML technique of Neural Network analysis with training of 70% observations. The paper will provide opportunity for other researchers to explore techniques of AI/ML in trade studies. [ABSTRACT FROM AUTHOR]

Forecasting energy demand accurately is the basis for the formulation and implementation of energy planning. In this paper, energy demand influencing factors are mainly decomposed into scale economy effect, population size effect, energy structure effect, and residential consumption effect based on the Logarithmic Mean Divisia Index (LMDI). Then, the Cointegration and Granger Causality tests are used to discover the influencing factors of energy demand in China. On this basis, a hybrid optimization algorithm, the least-squares support-vector regression optimized by particle swarm optimization (PSO-LSSVR), is proposed to forecast the energy demand of China. Then, three scenarios are set up to analyze the further development of drive factors of energy demand. Finally, in accordance with the forecasting results, some suggestions related to China's energy development policy are given. The main results are as follows. First, gross domestic product (GDP), the total population at the end of the year (POP), the coal consumption ratio in energy (CCR), and residential consumption levels (RCLs) are dominant indicators of energy demand in China. Second, the improved PSO-LSSVR model has significant superiority than other models in energy demand forecasting, a complex and nonlinear system with small samples. Third, China's energy demand will peak in 2022, which is 4.9 million tce in all scenarios. [ABSTRACT FROM AUTHOR]

Research background: China's economic growth, however remarkable, is due to the Harrod-Domar nature of economic growth and, therefore, limited. The main limitation lies in the extension of the neoclassical growth model and the government need to decrease regional disparities using new migration, urbanization and social policy. Purpose of the article: It is the rising regional disparity in the total factor productivity to cause the income inequality increase (measured by GINI index) in China from 1952-2017. Our paper brings new insight into the main inequality determinants and causes in China, using a fractional integration modeling framework. Methods: Using fractional integration, we find total factor productivity (TFP), real gross domestic product per capita and growth and expenditures for the social safety net and employment effort to have a statistically significant impact on GINI. Income inequality in China is of a persistent nature with the effects of the shocks affecting the GINI index enduring over time. Findings & value added: The results of this study highlight the importance for model/policy changes by the policy makers and practitioners in China to deal with the inequality issue. This involves improving the growth model through innovation and technological advancement, relaxing TFP dependence on the physical inputs (labor and capital) to reduce income inequality. [ABSTRACT FROM AUTHOR]

This paper examines how China has been portrayed in international cinema throughout the twentieth and twenty-first centuries. Using the Internet Movie Database, the authors extract the plot synopses of 4,927 China-related films. The authors apply the word embedding technology and Latent Dirichlet Allocation (LDA) topic model to explore the cinematic plots, as well as achieve the sentiment score and ascertain the socioeconomic factors of score change. The findings indicate that the image of China in international cinema has been associated with gross domestic product (GDP) and foreign direct investment. The image of China changed from the barbarian to the schemer, and finally to the civilized great power, giving the insight into cultural trends that traditional research methods cannot capture. [ABSTRACT FROM AUTHOR]

China, with a continuous existence of more than four millennia, represents one of the oldest civilisations in world history. Today's People's Republic of China is the second economic superpower of the world. It is not only the second-biggest economy in the world but also the largest trading nation. The aim of our paper is twofold: on the one hand, to define the concept of economic growth and, on the other hand, to briefly present and analyse China's economic growth since Xi Jinping has taken the power in 2012. In this sense, the author used a qualitative research method. The paper demonstrated that China's economic growth constitutes one of the most important issues on Xi Jinping's agenda. Also, it showed that in the past decade the Asian colossus attained remarkable achievements in the evolution of its gross domestic product and growth rate. [ABSTRACT FROM AUTHOR]

Carbon emissions in the power sector are an important part of China's total carbon emissions and have a significant impact on whether China can achieve the 2030 carbon peak target. Based on the three perspectives of decomposition, decoupling, and prediction, this paper studies the feasibility of carbon emission peaks in eight major regional power sectors in China. First, the generalized Divisia index model (GDIM) is used to decompose the carbon emissions of the eight regional power sectors, and the driving factors and their effects on carbon emissions in the power sector of each region are compared. Then, the decoupling index based on the generalized Divisia index model (GDIM-D) is used to study the decoupling relationship between the carbon emissions of the eight regional power sectors and economic growth. Finally, the carbon emissions and decoupling indices of the power sector from 2017 to 2030 are predicted. The results show the following. First, the gross domestic product (GDP) and output scale are the main factors contributing to the carbon emissions of the eight regional power sectors. The carbon intensity of the power sector in GDP (C/G) and output carbon intensity(C/E) are the main factors that contribute to the reduction. Second, the carbon emissions of the southern coast, the middle Yellow River, and the Southwest peaked in 2013 and have been decoupled from economic growth, while those in the other regions have not peaked or decoupled. Third, if the carbon emissions of the power sector in the Northeast, northern coast, eastern coast, middle Yangtze River, and Northwest reach a peak in 2030, they will face many emission reduction pressures. This paper provides a reference for studying the carbon emissions of China's regional power sectors and their relationship with economic growth and has important implications for peak carbon emissions at the national level. [ABSTRACT FROM AUTHOR]

Top-down place-based competition and award (TDPBCA) has a growing presence in the West and a long existence in China. TDPBCA refers to the motivational strategy in which a higher authority sets a series of targets for lower-level governments to compete against each other or to pass the benchmarks set by the higher authority to become a winner. The participants (unit of assessment) are 'places' at the same level of jurisdiction (countries, cities, neighbourhoods, villages). This paper examines TDPBCA as a local motivation policy tool. It first reviews the literature on different local stakeholder motivation strategies and theorises the motivational impact of TDPBCA. The paper then examines the usage of TDPBCA in China and its influence on local stakeholders' behaviour in terms of public participation, intersectoral collaboration, inter-regional learning and local public spending. The proposed paper examines TDPBC as a local motivation policy tool in China. The first section reviews the literature on different local stakeholder motivation strategies. The second section discusses theoretically the motivational impact of TDPBC. The paper then examines the usage of TDPBC in China and discusses its influence on local stakeholders' behaviour in terms of public participation, inter-sectoral collaboration, inter-regional learning and local public spending. [ABSTRACT FROM AUTHOR]

This paper analyzes the relationship between meteorological catastrophic factors and gross domestic product (GDP) growth rate of Nanjing city (China). The sample spans the period 1980-2010, including GDP growth rate and meteorological catastrophic factors (extreme precipitation, extreme temperature and extreme wind speed). We utilize econometric methods to take co-integration analysis and Granger causality test among GDP growth rate and the time series of meteorological catastrophic factors of Nanjing city processed by buffer operators. Finally, the paper shows the short-term changes in minimum atmospheric pressure, extreme high temperature, and minimum relative humidity, which has a positive impact on GDP; the cumulative effect of extreme precipitation and GDP affects each other to some extent, they are mutually Granger causes. Moreover, at the 95 % confidence level, we believe that maximum wind speed is the Granger causation of GDP growth rate. [ABSTRACT FROM AUTHOR]

This paper explores the non-technological innovation system for building low-carbon cities in China. It establishes a comprehensive evaluation index system and grading standards for low-carbon cities, concerning both technological innovation and non-technological innovation factors. Defining non-technological innovation factors as independent variables, GDP per capita as the main control variable, and low-carbon development and carbon productivity as dependent variables, this paper examines the contribution of non-technological innovation to the building of low-carbon cities. The result shows that non-technological innovation manifested a significant trajectory of progress. It demonstrates that the continuous improvement to non-technological innovation system should effectively promote the further development of low-carbon cities. [ABSTRACT FROM AUTHOR]

In this paper, first, we measure Chinese time preferences as a whole and by region based on the Euler equation under an assumption of rational expectation. The calculating results show that the rates of Chinese time preference are markedly low for most hypothetical risk attitudes over the concerning period, and there exists heterogeneity in time preferences across regions in China. Second, compared with the estimates for other advanced and emerging countries under the same assumptions and same methodology, the rates of Chinese time preference are the lowest for any given risk preference, suggesting that Chinese are more patient during the time of our examinations. Third, our measured time preferences are powerful in predicting China's high saving rates and rapid growth rates of gross domestic product. In addition, the differences in economic growth rates between China and other sample countries can be partially explained by the differences of estimated cross‐countries time preferences within our sample period. Fourth, we investigate the additional factors that affect the Chinese time preferences. Our study provides insights on the regional and international differences in economic growth rates and other economic outcomes. [ABSTRACT FROM AUTHOR]

Taxi fare is related to the daily life of residents. Reasonable taxi fare not only meets the travel demand of residents but also improves the income of drivers and promotes employment. The spatial variation of taxi fares exists between different regions and cities. Previous studies on taxi fares have been conducted mostly in individual cities, and there has been no study on the spatial differentiation pattern of taxi fares on a national scale. Taking 336 cities across China as the research object, a multiple linear regression model of taxi fares was established by demonstrating the spatial variation pattern of taxi fares, the global differentiation index, spatial autocorrelation analysis, and kernel density analysis, etc. The significance of the study is to explore the law of spatial differentiation of taxi fares in China and to provide a stenographic record of taxi fare adjustment. The results show that: (1) the spatial variation of taxi fares across the country is significant, with the starting taxi fare range being between RMB 4 and RMB 14. (2) The global differentiation index of taxi fares is large, with two low-low clusters and three high-high clusters appearing spatially, and the results of the kernel density analysis surface a dispersion distribution centered on provincial capitals. (3) The divergence pattern of taxis nationwide is influenced by several factors. A multiple linear regression model is selected to establish a multiple linear regression model of urban disposable income per capita, regional GDP, urbanization rate, and urban population density, which shows that urban disposable income per capita has the greatest influence on taxi fares. The model shows that urban disposable income per capita has the greatest influence on taxi fares, and the fare of a 5 km taxi ride is 6.07. Taxi fares have a clear pattern of spatial differentiation in China and are most affected by urban disposable income per capita. Through this study, we can gain a deeper understanding of the variation in taxi fares across the country and provide data and theoretical support for the rationality of taxi fare adjustments. [ABSTRACT FROM AUTHOR]

This article tests several predictions of tournament theory on executive compensation in the context of a transition economy. Using an unbalanced panel of 34,701 executives in 1,386 public listed firms in China during 1999 and 2006, the paper finds that (1) pay increases as executives move up the corporate hierarchy into higher ranks; (2) pay gap is the largest between the first- and second-tier executives; (3) pay dispersion increases with the number of tournament participants and the risk of the business environment; (4) state ownership of shares reduces pay, pay gap and the sensitivities of the contestant pool and business risk to pay dispersion; (5) board composition and independence, CEO duality and the independence of the supervisory committee all affect pay and pay dispersion. Overall, this paper shows that listed firms in China, as they become more and more market-oriented, have adopted a pay structure that is largely consistent with the predictions of tournament theory, and that it is important to consider both state ownership and corporate governance in analyzing executive compensation structure. [ABSTRACT FROM AUTHOR]

Developing Asia has traditionally relied on exports to the United States and other industrialized countries for demand and growth. As a result, the collapse of exports to the United States and other industrialized countries during the 2008-09 global financial crisis has sharply curtailed GDP growth across the region. The emergence of the People's Republic of China (PRC) as a globally influential economic force is fueling hopes that it can supplement the United States as an additional source of demand and growth. The central objective of this paper is to investigate whether exports to the PRC has a significant and positive effect on the GDP of eight developing Asian countries. Although the study's results indicate that exports to the PRC contributed to developing Asian countries' recovery from the global crisis, it is far too early to make well-informed judgments about the PRC's ability to support Asia's growth in the medium and long term. [ABSTRACT FROM AUTHOR]

The article reports that Research and Markets Ltd. has announced the addition of the new report "China Paper and Forest Products Market" to its offerings. According to the report, the Chinese government in 2004 has implemented broad macroeconomic regulations to curb its overheated industries and slow down fixed asset investment growth. The gross domestic product of China increased in 2004 and as a result, their papermaking industry saw positive developments.

Over the previous two decades, Chinese economic development presented a rapid growth. However, with continuous industrialization and urbanization, China is confronted with great challenges of energy security and environmental issues. These problems are closely related to the current accounting method of economic growth to a certain extent. In order to meet these challenges, it is imperative to establish a green accounting system of economic growth and measure China's green GDP and its changing trend based on the industrial perspective. Using the System of Environmental Economic Accounting (SEEA) and industry data, this paper estimates China's green GDP and green value added by industry sectors in 2005, 2007, 2010, 2012, 2015, and 2017. The results reveal the following: First, the ratio of green GDP to traditional GDP gradually increases from 89.85 to 95.83% during 2005–2017, which means that the negative externalities of economic growth of the resource and environment are gradually weakened. Second, the difference between traditional GDP and green GDP during 2005–2017 is about 6.96%, with the carbon emissions accounting for 70.71% of environmental impact. Third, due to more than 80% of the environmental impact coming from three sectors: manufacturing (49.99%), electricity industry (22.63%), and other services (11.37%), these three sectors should be key sectors for energy conservation and emission reduction; fourth, the green GDP of the mining, electricity industries, and manufacturing accounts for the lowest proportion of GDP, which means that the development patterns of these three industries in recent years should be adjusted and optimized step by step. [ABSTRACT FROM AUTHOR]

As a model based on the harmonious development of society, economy, population, and resources, sustainable development is an essential driving force for a country's social and economic development. The countryside is an important part of the country, and its sustainable development has been given attention, but existing research lacks a focus on the sustainable development of rural settlements in mountainous areas. In this paper, the rural settlements in the Miaoling Mountains of China are taken as the research object, a geographic detector is used to determine the weight of rural settlement sustainable development factors, a rural settlement sustainable development model is constructed, and a local spatial autocorrelation method is used to quantitatively analyse the level of sustainable development of the rural settlements and the influencing factors related to both the natural environment and socio-economic levels. The results show that (1) 78% of rural settlements in the Miaoling Mountains have a medium to low level of sustainable development and are weak in overall sustainability. (2) The spatial differentiation of the sustainable development levels of rural settlements in the Miaoling Mountains are apparent, and the high sustainable development level settlements are mainly distributed around the urban areas. In contrast, the low sustainable development level settlements are scattered. (3) The level of sustainable development is positively correlated spatially with gross domestic product (GDP), arable land, elevation, normalised difference vegetation index (NDVI), water systems, and roads, and negatively correlated spatially with slope. Of these, GDP, arable land, and elevation have a more substantial influence on the level of sustainability of rural settlements. According to the local autocorrelation analysis, the positively correlated settlement types are mainly clustered in distribution, while the negatively correlated settlement types are sporadic. [ABSTRACT FROM AUTHOR]

Due to international fragmentation, production increasingly occurs in global supply chains (GSC). The common belief is that this leads to more specialization, which implies more concentration of imports and exports over time. In this paper, we empirically test this hypothesis by analysing the geographical and sectoral concentration of GSC over the period 1995–2011. We adapt the traditional Herfindahl's concentration indexes to a multi-regional input–output framework. Taking the information on intersectoral and interregional linkages into full account gives the concentration indexes of GSC. The indexes are at different aggregation levels, which enables us to examine both geographical and sectoral concentration patterns. After that, we analyse the effect a country's geographical and sectoral concentration on its gross domestic product (GDP) per capita. Our findings are: an increase of geographical and sectoral concentration of GSC from 1995 to 2011; a growing role in global production chains played by China and other Asian countries; less concentration for European Union countries; a significant positive effect of geographical concentration on GDP per capita; and a significant negative effect of sectoral concentration. [ABSTRACT FROM AUTHOR]

This paper evaluates the debate over whether China's emergence as an economic superpower has been a complement or threat to ASEAN by examining data in the eleven years following China's accession to the WTO. Employing a qualitative approach, it seeks to understand whether China's growing dominance has hindered ASEAN GDP growth, exports and attractiveness as a destination for FDI. The evidence suggests that China's rise has caused a shift in global trade patterns, with China dominating Western markets at the expense of ASEAN countries. Despite this, China's dominance does not appear to have had a significant negative effect on growth rates for ASEAN GDP, exports, or FDI stocks. Given this, the paper concludes that while China is crowding ASEAN out of Western markets, increased Chinese demand for ASEAN imports has more than offset this effect. The result is that ASEAN exports and GDP have grown despite shifting trade patterns in the short run. [ABSTRACT FROM AUTHOR]