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Designing inter-regional and inter-provincial responsibility-sharing mechanisms for climate change mitigation requires the knowledge of carbon distributions. This study is the first to use a two-sector (i.e., productive and household sectors) inequality decomposition approach to examine the regional, provincial, and national inequalities of per capita CO2 emissions (CPC) in China, as well as their determinants. We show that the CPC inequality index in China increased from 1.1364 in 2000 to 2.3688 in 2017, with the productive sector accounting for 91.42% of this expansion and households responsible for the rest. The production-side per capita output level, energy efficiency, energy structure, and industrial structure explain 69.01%, 12.81%, 5.57%, and 4.03% of these inequalities, respectively. Further, the household per capita energy consumption and energy structure explain only 8.12% and 0.46%, respectively. Therefore, future responsibility-sharing mechanisms for climate mitigation need to be formulated taking mainly the productive sector into account. [ABSTRACT FROM AUTHOR]

The coordination of the relationship between new-type urbanization (NTU) and carbon emission reduction has become China's primary strategic goal. However, previous studies on this topic mainly examined the unidirectional impact of NTU on carbon emissions, while disregarding their potential relationship. This study establishes an evaluation system for measuring NTU and explores the bidirectional impact between NTU and total carbon emissions (TCE), per capita carbon emissions (PCE), and carbon emission intensity (CEI). The Yangtze River Economic Belt of China is selected as the study area, and the period from 2005 to 2019 is studied. The results show that: (1) The NTU levels in the upstream, midstream, and downstream regions of the Yangtze River increase from 0.148, 0.208, and 0.365 in 2005 to 0.465, 0.503, and 0.675 in 2019, suggesting that NTU levels tend to be balanced in these three reaches. (2) A positive bidirectional impact is found between NTU and TCE, as well as PCE in midstream and upstream regions, whereas in downstream regions, only a positive unidirectional effect of NTU on TCE and PCE is found. (3) Specifically, TCE plays the most significant role in promoting NTU in upstream regions, while NTU exerts the greatest pulling force on TCE and PCE in midstream regions. (4) Unlike the positive impact between NTU and TCE or PCE, there is a significant two-way inhibitory effect between NTU and CEI. (5) A three-step carbon emission reduction law is found in the process of NTU, where NTU towards low carbon development will experience NTU inhibits CEI, PCE, and TCE in sequential order. These findings provide an important reference for promoting a harmonious relationship between NTU and carbon emission reduction, helping governments formulate reasonable measures to achieve high-quality urban development and carbon emission reduction goals. • Bidirectional impact between new-type urbanization and carbon emissions of the Yangtze River Economic Belt is examined. • New-type urbanization positively affects total carbon emissions and per capita carbon emissions. • Negative bidirectional impact between new-type urbanization and carbon emission intensity is observed. • Regional heterogeneity of the impact between new-type urbanization and carbon emissions is found. [ABSTRACT FROM AUTHOR]

With the advancement of industrialization and urbanization, the issue of water shortage has become a bottleneck for China's economic development. Based on the structural decomposition analysis and multi-regional input–output tables of China in 2002 and 2012, this paper explores the drivers of the change in China's production water usage from the regional relevance perspective. Results show a significant increase in China's production water usage during the study period. The relationship between production water usage and per capita GDP shows an inverted U-shaped curve, and the economic scale by provinces has been improved, while the trend of production water usage differs. There are rapid increases in production water usage in economically developing provinces, while it is falling sharply in developed provinces. The crucial factors promoting its growth are changes in consumption level, population scale, and regional economic patterns. The technical effect is the most important factor in curbing the growth, followed by effects of final demand sectoral and distribution structure. The provinces and sectors with more production water usage shows higher technical and final demand effects. Therefore, it is necessary to promote water-saving activities, enhance the water-saving technical effect, and optimize final demand structure to promote economic growth with low-water usage. [ABSTRACT FROM AUTHOR]

It is of great significance to understand the spatial non-equilibrium and the solidification degree of transportation carbon emissions, so that differentiated measures can be taken to reduce transportation carbon emissions. Based on China's provincial data from 2005 to 2015, this article uses the Dagum Gini coefficient to decompose the spatial non-equilibrium of per capita transportation carbon emissions from static viewpoint. The results indicate that the overall spatial non-equilibrium shows a significant downward trend; the intensity of transvariation has had an increased contribution rate year by year since 2008, and replaces the inter-regional differences as the main source of the overall spatial non-equilibrium. Next, Kernel density estimation is employed to analyze the evolution laws of spatial non-equilibrium from dynamic viewpoint. The results show that the per capita transportation carbon emissions in the eastern region are successively higher than those at the national level, and in other regions. Meanwhile, some provinces are concentrated at a low level, while others at a high level. Finally, Markov chains approach is applied to identify the solidification effect of the spatial non-equilibrium. The results indicate that the effect is obvious and the state transitions occur only between adjacent types. Moreover, the solidification effects of the provinces with higher per capita transportation carbon emissions are stronger than those provinces with a lower level. [ABSTRACT FROM AUTHOR]

This article explored the long-run relationship between financial development and income inequality at the provincial level. In contrast with the intuitive hypothesis that financial deepening helps reduce the inequality, the provincial data reveal that financial deepening cannot improve the inequality. Instead, it makes the inequality worse. Since this result implies that financial development can increase GDP per capita and also increase income inequality, China is not passing the turning point of the inverted U-shaped curve yet. This is consistent to the fact that China is a developing country. [ABSTRACT FROM AUTHOR]

This paper performs a comparative analysis of the Chinese and Mexican production structures, through a descriptive study and using the methods of structural analysis on input-output tables of 1995 and 2011. During this period, the average annual per capita gross domestic product (gdp) growth in China amounted to 9.18%, while in Mexico it reached only 0.95%. Assuming that China's growth has been successful in this sense, then a mayor conclusion from this paper is that if Mexico wishes to reach high growth rates, the main element potentially useful to elaborate an efficacious strategy from China's experience is clear: To foster, from a proactive participation of the state, the development of key sectors which will constantly increase their multiplier effects, so that a mayor integration of the national economy is achieved, and the development and consolidation of the productive apparatus sufficient to support the generation of next-generation productive sectors. [ABSTRACT FROM AUTHOR]

This paper has used a stirpat model to investigate the synergistic effect of CO2 emission, energy consumption, energy intensity, economic growth, population, urbanization and trade openness to demonstrate growthenvironment nexus in four selected developing Asian economies. Taking a panel data set from Bangladesh, China, India and Indonesia this study applies Autoregressive Distributed Lag (ardl) model and vec Granger Causality/Block Exogeneity Wald Tests. The empirical results show that energy intensity, urbanization, population, and per capita gdp growth are the raison d'être of CO2 emissions whereas trade openness is found to be negatively related to CO2 emissions. Conversely, energy consumption, urbanization, population and trade openness are positively related to per capita gdp. In addition, it also investigates the Environmental Kuznets Curve (ekc) hypothesis and the findings substantiate an inverted Ushaped relationship. Cross-section short-run coefficients of country-level data are inquired into to check the robustness of the panel outcomes. [ABSTRACT FROM AUTHOR]

As the largest carbon dioxide (CO2) emitter, China exists obvious regional inequality in per capita CO2 emissions. However, such inequality and its dynamic change for recent years have not been systematically studied. In this paper, we evaluate China's regional inequality in per capita CO2 emissions during 1997–2016 using the Theil index and decompose it into within-region and between-region components based on eight regions. Furthermore, we apply the decomposition analysis to explore the contribution of different factors to such inequality, including the carbonization index, energy intensity, energy structure, labor productivity, and employment rate. The results show that China's overall inequality in per capita CO2 emissions reduced first and increased thereafter during 1997–2016. Within-region inequality was the main source of overall inequality in 1997–2004, while between-region inequality contributed more during 2005–2016. Labor productivity and energy intensity were the two main drivers of overall inequality, but their contributions to the inequality between regions and within regions were quite different. Moreover, the impact of energy structure and carbonization index on regional inequality in per capita CO2 emissions significantly increased during 2012–2016, which was related to the efforts made by local governments to improve the energy mix. Policy implications were given according to the above conclusions to improve regional inequality in per capita CO2 emissions. [ABSTRACT FROM AUTHOR]

Rapid urbanization in China has led to an increasing imbalance in regional development. The Guangxi Zhuang Autonomous Region, a less developed border province with unique cultural diversity, has a relatively large population (4.52 million people in 2015) under the poverty line, according to the national standard of poverty. China has launched a national campaign to reduce poverty using a wide range of new development policies and large-scale investment. However, there have been few studies on the determinants of poverty at the county level across a province. This paper aims to explore the spatial and social differences related to poverty among 109 counties by considering the spatial heterogeneity of poverty determinants. Spatial statistical models revealed that slope (Slp), GDP per capita (GDPP), the ethnic minority population ratio (EMPR), medical and technical personnel of healthcare institutions (MTP) and illiteracy rate (IR) significantly affect the patterns of the poverty rate, with a high adjusted R2 (0.67), while the poverty rate affects GDPP, IR, MTP and EMPR; i.e., the effects are interactional. Furthermore, the IR is significantly affected by the provision of schools and transportation conditions. Among these determinants, social factors may be key. The spatial patterns of these relationships demonstrate remarkable variation across the province and between minor and major groups. This quantitative evidence is enhanced by indepth interviews with selected groups. These results are expected to be useful for the anti-poverty project in Guangxi. [ABSTRACT FROM AUTHOR]

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The rapid increase in anthropogenic activities, socioeconomic development, and land use land cover (LULC) changes since the opening of economic reforms (1978), have changed the ecosystem service value (ESV) in Guangdong, Hong Kong, and Macao (GKHM) region located in South China. This leads to the requirement of a significant tailored analysis of ecosystem services regarding incisive and relevant planning to ensure sustainability at regional level. This study focuses on the use of Landsat satellite imagery to quantify the precise impact of LULC changes on the ecosystem services in GHKM over the past three decades (1986–2017). The most renowned established unit value transfer method has been employed to calculate the ESV. The results show that the total ecosystem service value in GHKM has decreased from 680.23 billion CNY in 1986 to 668.45 billion CNY in 2017, mainly due to the decrease in farmland and fishponds. This overall decrease concealed the more dynamic and complex nature of the individual ESV. The most significant decrease took place in the values of water supply (-22.20 billion CNY, -14.72%), waste treatment (-20.77 billion CNY, −14.63%), and food production (-7.96 billion CNY, −33.18%). On the other hand, the value of fertile soil formation and retention (6.28 billion CNY, +7.26%) and recreation and culture (5.09 billion CNY, +12.91%) increased. Furthermore, total ESV and ESV per capita decreased significantly with the continuous increase in total gross domestic product (GDP) and GDP per capita. A substantial negative correlation exists between farmland ESV and GDP indicating human encroachment into a natural and semi natural ecosystems. The results suggest that in the rapidly urbanizing region, the protection of farmland and to control the intrusion of urban areas has marked an important societal demand and a challenge to the local government. This required a pressing need for smart LULC planning and to improve policies and regulation to guarantee ecosystem service sustainability for acceptable life quality in the study area and other fast expanding urban areas in China. [ABSTRACT FROM AUTHOR]

With rapid economic and population growth, construction land expansion in Yangtze River economic belt in China becomes substantial, carrying significant social and economic implications. This research uses Expansion Speed Index and Expansion Intensity Index to examine spatiotemporal characteristics of construction land expansion in the Yangtze River economic belt from 2000 to 2017. Based on a STIRPAT model, driving forces of construction land expansion are measured by Principal Component Analysis and Ordinary Least Square regression. The results show that: (1) there is a clear expansion pattern regarding the time sequence in provinces/cities of the Yangtze River economic belt, with rapid expansion in the initial stage, moderate expansion in the middle stage and rapid expansion in the later stage. (2) Spatial analysis demonstrates first expansion in the lower reaches in the early stage, rapid expansion of the upper reaches in the middle and later stage, and steady expansion of the middle reaches throughout the research period. (3)There are statistical significant correlations between construction land expansion and GDP, social fixed asset investments, population at the end of the year, population urbanization rate, per capita road area, and number of scientific and technological professionals as well as secondary and tertiary industry values. Of these factors, GDP, social fixed asset investments, population urbanization rate and second industry value are important common driving forces of construction land expansion in this region. The research findings have significant policy implications particularly on coordinated development of urban agglomerations and sustainable industry upgrading when construction land expansion is concerned. [ABSTRACT FROM AUTHOR]

Low-carbon development is an essential measure to combat climate change, and the establishment of low-carbon standards is an important means to achieve low-carbon development. Due to the differences in size and development level among counties of China, the applicability and fairness of county-level low-carbon standards are very important in this country. This study analyzed the trends of county-level carbon emissions in China, defined the peak value of carbon emissions per capita, summarized the characteristics of existing low-carbon standards, and proposed a fair county-level low-carbon standard based on carbon emissions per capita. The results of our analysis suggest that, under the constraints of carbon emissions reduction policies, China's carbon emissions per capita will tend towards a stable range. Additionally, by referring to predictions results of the peak value of China's carbon emissions per capita, it was determined that, in low-carbon development targets, China's county-level carbon emissions per capita should be set within the range of 2–4 tons. Besides setting low-carbon standards, the Chinese government and private enterprises should develop low-carbon technologies as soon as possible and innovate management models to achieve the win–win situation of simultaneous economic growth and carbon emissions reduction. [ABSTRACT FROM AUTHOR]

Assessing urban environmental sustainability is fundamentally important for guiding urban areas to achieve more sustainable urban development. We followed the theme-oriented framework to select eight indicators for measuring urban environmental sustainability performance in China using three aspects: waste emissions, resource consumption, and environmental initiatives. These eight indicators were measured per unit area, per capita, and per GDP for 286 prefecture-level cities, 22 urban clusters, and 7 geographic regions of China from 2000 to 2010. Among the 7 geographic regions, the East China region had the greatest intensity of waste emissions, resource consumption, and environmental investment per unit area. In comparison, the Central China region had greater water consumption and wastewater discharge measured per capita and per GDP. The North China region had greater waste gas emissions and energy consumption measured per capita and per GDP than the other regions. The three northern regions of China (North China, Northeast China, and Northwest China) also had the greatest solid waste emissions measured per capita and per GDP. The expansion of the built-up area per GDP was the greatest in the western regions (including Northwest China and Southwest China), indicating a very low urban land-use efficiency for these two regions. Among the 22 urban clusters, the 12 well-developed urban clusters had greater waste emissions, resource consumption, and environmental investment per unit area than the 10 less-developed urban clusters. The well-developed urban clusters also had larger environmental investment as a share of GDP than the less-developed urban clusters, but waste emissions and resource consumption per GDP were much lower for the well-developed urban clusters. Among the 286 prefecture-level cities, the cities with greater waste emissions and resource consumption per unit area also had greater environmental investment per unit area, but these cities increased their environmental investment at a relatively slower rate than the increase in their waste emissions and resource consumption. The cities that spent a larger share of GDP on pollution reduction had relatively lower waste emissions per GDP, but more investment should be targeted at improving resource efficiency, especially for those resource-intensive cities. In summary, the well-developed urban clusters and cities in the eastern region of China generally had much greater waste emissions and resource consumption per unit area (i.e., greater impacts), while they had lower waste emissions and resource consumption per capita and per GDP (i.e., higher efficiency) relative to the less-developed urban clusters and cities in central and western regions. Based on these findings, we proposed several countermeasures for improving urban environmental sustainability for different cities, urban clusters, and geographic regions of China. • We provided an assessment framework and an indicator set for measuring Urban Environmental Sustainability (UES). • We compared UES performance among 286 prefecture-level cities, 22 urban clusters, and 7 geographic regions of China. • We proposed several countermeasures for improving UES in China. [ABSTRACT FROM AUTHOR]

Urbanization is an important direction for China's future social development and an important focus of its carbon emission reduction path. China's current administrative management is a vertical nested structure, and the characteristics of high-scale regions have a non-negligible impact on low-scale areas. Taking the county scale of the basic unit of economic and social development as the research scale, according to the panel data of the Yangtze River Delta from 2008 to 2016, a two-level hierarchical linear model (HLM) for carbon emission intensity is constructed, especially considering the characteristics of high-scale regions (i.e., low-carbon pilot cities) at the second level, and is combined with the mediating effect test method to analyze the impact path of urban development on carbon emissions intensity. The results show that (1) there is a spatial nesting relationship between regions of different scales, and the city scale can explain 85.21% of the carbon emissions intensity, which is much higher than the county scale. (2) There is an N-shaped curve relationship between urban development and carbon emissions intensity. After considering the high-scale factor (low-carbon pilot cities) at the city scale (the second level of the HLM), if a high-scale city is a low-carbon pilot city, then improvement in the level of urbanization in the county can promote a reduction in carbon intensity. (3) The impact path of urban development ⇄ per capita gross domestic product (the proportion of secondary industry, patent application volume) → carbon emissions intensity and urban development → the proportion of tertiary industry → carbon emissions intensity is significant. However, the path of the proportion of tertiary industry → urban development → carbon emissions intensity is not significant. [ABSTRACT FROM AUTHOR]

Understanding the food choices of local people is key to identifying practical opportunities for sustainable dietary change. Here, we assess the dietary pattern and environmental impacts of Chongqing hotpot in China, a local food in the Szechuan Basin enjoyed by ∼110 million people primarily in restaurants with an increasing popularity nationwide. Through a yearlong survey, we find that hotpot meals are characterized by overconsumption (588.7 g/cap/meal), especially of animal-based products (∼70%). The embedded carbon footprint (CF) of hotpot reaches 3.5 kg CO 2 e per capita per meal; by contrast, the CF of recommended diets per capita per day in China is 2.3–3.7 kg CO 2 e. Its water footprint shows a similar trend. Hotpot meals are also more wasteful than other types of restaurant food (80.4 vs. 54.1–75.0 g/cap/meal). Our study raises concern about the environmental impacts of Chongqing hotpot. To mitigate these impacts, intervention strategies that should be considered include small-portion plates and plant-based meat alternatives. [Display omitted] [ABSTRACT FROM AUTHOR]

• The accuracy of methods to calculate the global distribution of income has not yet been tested. • Among four methods, the Lorenz-curve regression method is the most accurate. The two-parameter distribution method is also very precise. • On the basis of our new dataset, we find that income inequality among the citizens of 145 countries declined significantly between 1988 and 2015. • Our new method to deconstruct the change in the global Gini coefficient of income inequality reveals that income convergence was the main driver. • Without China and India, global interpersonal income inequality in 143 countries was higher in 2015 than in 1988. While various methodologies have been used in the literature to estimate global interpersonal income inequality, the accuracy of these methods has not so far been tested. We compare the accuracy of four methods and find that the Lorenz curve regression method is the most accurate and robust, while the accuracy of the identical quantile income and the Kernel density methods depends on the level of detail about income shares. The simple two-parameter distribution method is also very accurate when either the Log-normal or the Weibull distribution is used. Using the two-parameter distribution method, we show that global income inequality among the citizens of 145 countries declined significantly between 1988 and 2015, largely because of the convergence of income per capita, which was offset to a small degree by the increase in within-country inequalities and the increased population share of poorer and more unequal countries. Regional income inequality declined in most parts of the world, with the notable exception of developing Asia where it has increased. Despite the large increases in within-China and within-India inequality, income convergence of the two countries drove down global income inequality. Without China and India, global interpersonal income inequality in 143 countries was higher in 2015 than in 1988, indicating that more than half of the world has not really become more equal. [ABSTRACT FROM AUTHOR]

Purpose: This study aimed to measure the income-related inequality of depressive symptoms and its trends among middle-aged and elderly people in China.Methods: Data were extracted from the 2011 baseline and 2015 follow-up of the China Health and Retirement Longitudinal Study (CHARLS), a nationally representative survey for people aged 45 years and more. Depressive symptoms were evaluated with the Chinese version of the ten-item Center for Epidemiologic Studies Depression Scale. Five relative income levels were derived from ratios between the participants' annual per capita household expenditure, excluding medical expenditure, and the median PCE of their cities. The concentration curve and index were used to compare the magnitude of income-related inequality between 2 years. A logistic regression model was used to control the other socio-economic factors.Results: The prevalence of depression among middle-aged and elderly people in China decreased from 37.0% (5540 of 14,956 participants) in 2011 to 32.7% (5606 of 17,165) in 2015. However, the absolute value of the standardized concentration index increased from 0.005 to 0.028. Although the second lowest-income group had the greatest improvement in the decline of prevalence (5.7%, from 38.6 to 32.9%), the lowest-income group had only the minimal decline (2.4%, from 40.6 to 38.2%). In 2015, there were significant differences between the lowest-income group and other four groups while the differences among other four groups were not statistically significant.Conclusions: The prevalence of depression among the middle-aged and elderly in China is declining, but the issue of income-related inequality has been exacerbated. The fairness of mental health deserves more attention. [ABSTRACT FROM AUTHOR]

Civil buildings are among the structures that consume the most energy in society. Reducing the energy consumption of civil buildings has become an important component of China’s energy policy. Identifying the key influencing factors of the energy consumption of civil buildings and formulating effective energy-saving countermeasures are important to enhance the energy efficiency of civil buildings. This study conducted a systematic analysis of the influencing factors of the energy consumption of civil buildings in Hubei Province, China. First, existing studies on the influencing factors of the energy consumption of buildings in foreign developed countries were reviewed. The status of the population, economic life, and social life that influenced the energy consumption of civil buildings in Hubei Province in the past 10 years was summarized. Relevant influencing factors were estimated via ridge regression. Results demonstrated that developed countries generally investigated the influencing factors of the energy consumption of civil buildings from the energy supply-demand relation, family factors, and out-of-family factors. Gross domestic product (GDP), total population, tertiary industry development, per capita floor space, household consumption level, and urbanization facilitated the energy consumption of civil buildings in Hubei Province during the aforementioned period, and the regression coefficients were significant at the 5% level. Lastly, policy countermeasures were proposed to accelerate the energy-saving development of civil buildings. Research conclusions are important to enrich theories regarding the energy consumption reduction of civil buildings, to help relevant government sectors of Hubei Province recognize action points for the energy-saving development of civil buildings, and to accelerate the benign development of energy-saving buildings. [ABSTRACT FROM AUTHOR]

Numerous studies have examined the determinants of housing prices in Chinese cities. However, most of them ignored the hierarchical structural characteristics of housing prices because of the use of ordinary least squares and hedonic pricing to model the housing prices for a single city. Therefore, this study explores the multi-level determinants of housing prices and their interactions at different levels. To this end, it proposes a three-level hierarchical linear model (HLM) using observations from 146,099 communities nested in 1120 counties of 31 provinces in China as a case study. The results of the hierarchical linear regression indicate significant variances in average housing prices. This finding suggests HLM to be appropriate when dealing with housing prices inherently nested at multiple geographic levels. Overall, housing values in China are not only determined by accessibility factors but are also driven by multi-level socioeconomic aspects. Among the selected variables, high-speed railway shows a significant positive effect, while ordinary railway shows a significant negative effect on housing values at the community level. At the county level, rural–urban migration and per capita living space have significant positive impacts on housing value. At the province level, the relationship between rural–urban migration and housing prices depends on economic development and urban employment. Similarly, the average wages of urban employment influence the relationship between per capita living space and housing prices. These results suggest that contextual effects exist between the determinants of housing prices at county and province levels. [ABSTRACT FROM AUTHOR]

Inequality has been the subject of intense debates in China, but inequality across cities remains less studied. This article investigates economic inequality based on prefectural-level cities during the period from 1990 to 2010. Statistical analyses indicate that interregional inequality among cities has increased, which is mostly attributable to widening intraregional inequality, especially within the western region. The high gross domestic product (GDP) per capita clusters emerged in the Pearl River Delta in the 1990s, spread to the Yangtze River Delta in the 2000s, and then reached north China in the 2010s. In contrast, the number of low GDP per capita clusters significantly increased in the central and western regions in the 2010s. In addition, the significance of national development zones and foreign direct investment indicates the greatest effect of globalization on the increasing intercity inequality. Decentralization also contributes to the intercity inequality of China. We suggest that in addition to national programs aimed at reducing the inequality between the eastern region and the rest of China, efforts are needed to reduce inequality within each region through provincial and local government policies, especially in western China. Key Words: China, cluster, decentralization, globalization, regional inequality, urban inequality. [ABSTRACT FROM AUTHOR]

Although China's western cities have developed rapidly in recent years, their ecosystems remain fragile. The conflict between urban development and environmental protection must be resolved to achieve the goal of sustainability. This study examines Xi'an as a case study of a megacity in Western China, calculating the city development index (CDI) and per capita ecological footprint (ef) from 2005 to 2016 to comprehensively calculate Xi'an's eco-efficiency. The E-C elasticity coefficient, which refers to the ratio of the rate of change in CDI to the rate of change in ef , is proposed to characterize the degree to which urban development responds to changes in the ef. The CDI and ef both showed an upward trend from 2005 to 2016. Xi'an's environmental efficiency has grown rapidly, and resource efficiency is the main factor driving its fluctuations in eco-efficiency. The energy consumption and pollution emissions are highly correlated with the CDI, and they are the main factors affecting the development of Xi'an. The relationship between CDI and ef is consistent with the law of diminishing marginal utility, the level of urban development rises and then decreases with the increase in ef. • City development index is significantly related to ecological footprint. • Main factors affecting city development are energy consumption and pollution emission. • Resource efficiency is the main driver of eco-efficiency change in Xi'an. • Development of Xi'an rises and then falls with the increase in ecological footprint. • E-C elasticity coefficient was proposed to illustrate the process of city development. [ABSTRACT FROM AUTHOR]

Numerous environmental problems have been seen due to the "high energy consumption, high pollution, high emissions" economic model in the Beijing-Tianjin-Hebei urban agglomeration (BTHUA). The coupling coordination degree model is applied to provide a coordination of urbanization and ecological environment composite system (CUECS) value while a geographic detector is applied to explore the dominant factors controlling it. This study reached the following conclusions. (1)The CUECS types are mainly low coordination, but which generally exhibit positive evolutionary trend. The change trends can be characterized as urbanization lags followed by system equilibrium followed by ecological environmental lags. (2)The CUECS conforms to a core-edge distributional pattern that comprises plain high mountain low, inland high coastal low. Industrialization played a key role in the development of BTHUA, the landform type was the important factor controlling CUECS. (3) Social consumer goods, gross domestic product, the disposable income of urban residents (all per capita) are the core factors controlling CUECS within different spatial units. Urbanization rate, per capita social consumer goods, the proportion of tertiary industrial population are the core factors controlling CUECS during different urbanization development stages. (4)The relative impacts of urbanization and ecological environmental subsystems on CUECS are (in decreasing order of importance) population urbanization, economic urbanization, social urbanization, ecological environment subsystem. Therefore, green urbanization remains the primary path for sustainable development within the urban agglomeration. It is unsuitable for rapid urbanization development model in the mountainous areas that encapsulate ecological and environmental security as their main functions, so the government urgently needs to amend its 'one size fits all' policy system. • Coordination of urbanization and ecological environment composite system (CUECS) shows core-edge pattern with plain high mountain low, inland high coastal low. • Consumption, gross domestic product, income are core factors controlling CUECS within different spatial units. • Urbanization rate, consumption, service industry are core factors controlling CUECS during different urbanization stages. • Relative impacts on CUECS sort as population urbanization, economic urbanization, social urbanization, ecological environment subsystem. • Green urbanization remains primary path for sustainable development of urban agglomeration. [ABSTRACT FROM AUTHOR]

Numerous studies have explored the drivers and consequences of the expansion of urban areas. However, limited research has been conducted on the land development of cities based on the different developmental stages. Therefore, using land transaction records obtained by Python in the land market of China during the 2011–2015 period, this study explores the factors affecting the land development process in 289 cities at five different stages of economic development. The development stages are identified by combing per capita GDP and the industrial structure in the 289 cities in 2015. The stages of economic development are the primary production stage (PPS), primary industrialization stage (PIS), middle industrialization stage (MIS), later industrialization stage (LIS), and developed stage (DS). The results reveal that with the advance of regional development stage, the scale of land development increases. We also find that, in general, the proportions of residential and public management-service land development projects increases, whereas the proportion of transportation land development projects decreases. The proportions of industrial-mining-warehouse land development projects first increases and then decreases, and there is no significant change in the proportion of land used for commercial land development projects. Regression analyses of panel data indicate that various factors have different effects on land development at five developmental stages, although the positive effects of domestic fixed asset investment on land development are always strongest. The results can contribute to our understanding of land development patterns in different stages of development and local governments in China, and thus to the formulation of reasonable annual land development plans. • With the development of regional economy, the demand for construction land is increasing. • The differences of land development structure in different stages of economic development are also significant. • The impact of non-agricultural industrial development, capital accumulation and population growth on land development in different stages of economic development is also significantly different. [ABSTRACT FROM AUTHOR]

The convergence of carbon emissions in important regions is a key prerequisite for reaching China's carbon emissions peak target. The Yangtze River Economic Belt (YREB) is the latest strategic economic area in China. In this study, a method of investigating the convergence of per capita carbon emissions in the YREB is proposed, and it includes the following models: σ convergence, stochastic convergence and β convergence. Besides, the five control variables per capita Gross Domestic Product (GDP), energy consumption structure, industrial structure, population density and urbanization rate are considered in the test models. In addition to testing the whole sample of 74 cities belonging to the Economic Belt, the convergence of three subgroups (municipalities, capital and sub-provincial cities and prefecture-level cities) is also tested by considering spatial effects. The following results are obtained: (1) although σ convergence and β conditional convergence are observed, stochastic convergence is not observed for the 74 cities; (2) the per capita GDP and energy structure are the key factors influencing the cities' convergence, whereas the urbanization rate has a limited impact; and (3) improving the industrial structure and reducing the population density are effective methods of promoting the convergence of per capita carbon emissions among the capital and sub-provincial cities and municipalities, respectively. [ABSTRACT FROM AUTHOR]

• Consumers believe in shared environmental responsibility of different stakeholders. • Confidence in oneself and others increases Chinese's environmental behaviors. • Confucianism triggers perceived governmental and corporate responsibility. • Perceived responsibility of powerful others differs by GDP per capita. Many people think that only powerful institutions are effective to combat environmental problems, especially in government-guided countries such as China. This study contrasts people's beliefs in their own abilities to improve the environment to their perceptions of other powers (e.g. government, corporations, higher powers, and earth-cycles). Previous research explored the impact of internal and external control beliefs on individuals' pro-environmental behavior mostly separately in developed Western countries. Since China's cultural and sociopolitical environment significantly differs from that of Western countries, we develop and test an integrated model of environmental locus of control (ELOC) to enlighten possible interactions and simultaneous effects in China. As expected, results indicate that internal ELOC generates positive effects on Chinese people's behaviors. But contrary to our predictions, external ELOC is positively correlated with internal factors and also positively influences behaviors. The belief in one's own abilities outperforms the belief in others to translate the confidence into reported behaviors. Nevertheless, Chinese perceive a higher level of governmental and corporate responsibility relative to their own environmental impacts which is driven by Confucian values (i.e. group orientation, belief in hierarchy). Compared to relatively consistent internal ELOC, the perceptions of most external ELOC factors significantly differ among provinces by levels of GDP per capita. Promotional programs should stress the individual's significance through daily behaviors in specific ways such as green purchase, activism, advocate (e.g. persuasion of friends), and recycling. Communicating the impact of powerful institutions might not necessarily trigger responsibility diffusion, but seems to promote the sense of shared responsibility. [ABSTRACT FROM AUTHOR]

Impervious surfaces are the most significant feature of human settlements. Timely, accurate, and frequent information on impervious surfaces is critical in both social-economic and natural environment applications. Over the past 40 years, impervious surface areas in China have grown rapidly. However, annual maps of impervious areas in China with high spatial details do not exist during this period. In this paper, we made use of reliable impervious surface mapping algorithms that we published before and the Google Earth Engine (GEE) platform to address this data gap. With available data in GEE, we were able to map impervious surfaces over the entire country circa 1978, and during 1985–2017 at an annual frequency. The 1978 data were at 60-m resolution, while the 1985–2017 data were in 30-m resolution. For the 30-m resolution data, we evaluated the accuracies for 1985, 1990, 1995, 2000, 2005, 2010, and 2015. Overall accuracies reached more than 90%. Our results indicate that the growth of impervious surface in China was not only fast but also considerably exceeding the per capita impervious surface area in developed countries like Japan. The 40-year continuous and consistent impervious surface distribution data in China would generate widespread interests in the research and policy-making community. The impervious surface data can be freely downloaded from http://data.ess.tsinghua.edu.cn. [ABSTRACT FROM AUTHOR]

Abstract Background China and other developing countries in Asia follow similar economic growth patterns described by the flying geese (FG) model, which explains the "catching-up" process of industrialization in latecomer economies. Japan, newly industrialized economies, and China have followed this path, with similar economic development trajectories. Based on the FG model, we postulated a "flying S" hypothesis stating that if a country is located within an FG region and its energy matrix is relatively constant, its per capita CO 2 emission curve will mirror that of "leading geese" countries in the same FG group. Method Historical CO 2 emissions data were obtained from literature review and national reports and were calculated using bottom-up methods. A sigmoid-shaped, non-linear mixed effect model was applied to examine ex post data with 1000 simulated predictions to construct 95% empirical bands from these fits. By multiplying by estimated population, we predicted total emissions of selected FG countries. Results Per capita CO 2 emissions from the same FG group mirror each other, especially among second and third industrial sectors. We estimated an annual 18,252.24 million tons of CO 2 emissions (MtCO 2) (95% CI = 9458.88–23,972.88) in China and 8281.76 MtCO2 (95% CI = 2765.68–14,959.12) in India in 2030. Conclusion This study bridges the macroeconomic FG paradigm to study climate change and proposes a "flying S" hypothesis to predict greenhouse gas emissions in East Asia. By applying our theory to empirical data, we provide an alternative framework to predict CO 2 emissions in 2030 and beyond. Highlights • Per capita CO 2 emissions from developing countries in Asia follow economic growth patterns, described as flying geese model. • Per capita CO 2 emissions trajectory in one country can forecast the emissions in another, under two assumptions. • Our flying-S model provides business-as-usual scenario, predicting counterfactual CO 2 emissions without any intervention. • In 2030, we estimated more than 18 billion tons of CO 2 (BtCO 2) emission in China, and 8 BtCO 2 in India. [ABSTRACT FROM AUTHOR]

Highlights • Analyzes the influence of electricity consumption structure on carbon emissions. • Calculates the proportion limit value of coal power consumption for rail transit. • Quantitative analysis of carbon emission reduction potential of rail transit. • The greater the traffic demand, the greater the carbon emission reduction potential. Abstract With the rapid development of rail transit, a vast amount of electric power is consumed each year. However, the generation of electricity, and especially coal power generation, is an important source of greenhouse gases. Therefore, it is very important to analyze the potential of carbon emission reduction of urban rail transit based on specific electricity consumption structures. In this study, 18 cities in China were taken as the research object, and backward analysis was used to analyze the proportion limit of coal power consumption for rail transit in each city under three scenarios from 2015 to 2017. By comparing the limit value with the actual coal power consumed by urban rail transit, we analyzed the potential carbon emission reduction of rail transit relative to other traffic modes. The study results supported several conclusions. First, the traffic demand is in direct proportion to the carbon emission reduction potential in rail transit. Second, for cities with high coal power consumption, the development of ground bus transit is more conducive to achieving carbon reduction targets compared with rail transit. Finally, promoting the development of rail transit technology and lowering the energy consumption per capita unit travel distance are the fundamental ways to increase the emission reduction potential of rail transit. Therefore, as a modern transportation tool, rail transit is not an absolute emission reduction advantage for all cities. A city needs to analyze its own resource structure and travel demand together, set up suitable traffic modes to realize green growth and sustainable development. [ABSTRACT FROM AUTHOR]

Tourism is a worldwide industry, but the per capita share of tourism resources in China is relatively small, and the capacity of the tourism environment is limited. Achieving economic growth in tourism and preserving tourism resources and the ecological environment are the premise and guarantee of tourism’s sustainable development under the constraints of tourism resources and ecological environment. By calculating the coupling degree of the tourism industry and regional ecological environment, the coupling degree of the regional economy and environment in a particular area can be effectively determined, and a basis for promoting the coordinated development of tourism and ecological environment can be provided. Taking Henan Province as an example, this study establishes a comprehensive evaluation system of the coupling degree between the tourism industry and regional ecological environment system, and uses the coupling model to analyse the coupling status of the two subsystems in Henan Province, and proposes policy suggestions to promote the coupling development of the two subsystems. Results show that the tourism subsystem of Henan Province increased from 0.024 in 2010 to 0.862 in 2016, and the order degree of the ecological subsystem rose from 0.070 in 2010 to 0.770 in 2016. The orderliness of the eco-environment subsystem is less than that of the tourism subsystem, indicating that further improvement of the eco-environment in Henan Province is still possible. The coupling degree of the tourism industry and regional ecological environment showed an increasing trend annually from 0.169 in 2011 to 0.766 in 2016 and exhibited a particularly large increase in 2013. This study’s results can provide a theoretical reference for understanding the coordinated development between the tourism industry and regional ecological environment, promoting the coupling between them, and enhancing the sustainable tourism industry of Henan Province. [ABSTRACT FROM AUTHOR]

The spatial and temporal coupling relationship between rural residential land and population is the theoretical base for optimizing rural land resources. This paper aims to analyze the sequential variation characteristics, spatial heterogeneity rules and coupling relationship types of Chinese rural land resource and population. Demographic data and land survey data are analyzed with elastic coefficient model. The main research results include: 1) During 2007-2015, rural residential land linearly increased at an average annual rate of 1.94%, and totally increased 257.27×104 hm2. 2) Per capita residential land area of rural population and agriculture population increased at an average annual rate of 4.61% and 1.98%, respectively, and the gap between them was widen at an average annual rate of 16.2%. 3) The coupling relationship between rural residential land and rural population was type G (land area increase, population decrease and the former grows less rapidly than the latter) unbalanced development at national scale, and was type G or type H (land area increase, population decrease and the former grows faster than the latter) unbalanced development in all provinces. The coupling relationship between rural residential land and agriculture population was type H unbalanced development at national scale, and was unbalanced in 93.55% provinces. The research results indicated that the coupling relationship between rural residential land and rural population was unbalanced development in China during 2007- 2015. This research could provide scientific supports for optimizing rural land resources and promoting coordinated development of rural man-land relationship. [ABSTRACT FROM AUTHOR]

This study examines the energy efficiency transitions in China using provincial data covering the period 2003-2015. Sustainable progress in energy efficiency achievement is beneficial to energy security and the achievement of the Paris Agreement. This article combines the stochastic frontier method with the panel Markov-switching regression to model energy efficiency transitions. The estimated energy efficiency scores show significant regional and provincial heterogeneity. Also, while human capital development, urbanization, and foreign direct investment promote energy efficiency, price and income per capita reduce it. The transition probabilities indicate that the high energy-efficient state is less sustainable, and the movement towards the frontier seems less persistent than movement from the frontier. Thus, it appears that China is not making sustainable progress in energy efficiency. The unsustainable nature of the high energy-efficient state suggests that in China, there are weak energy efficiency efforts and energy efficiency policies lack robustness. [ABSTRACT FROM AUTHOR]

Following three decades of rapid but unbalanced economic growth, China's reform agendas are set to rebalance the economy towards consumption while maintaining strong GDP growth. Headwinds include a demographic contraction that will bring negative labour force growth and rapid ageing. Rising aged dependency combined with lower saving rates will rebalance the economy, but they will reduce both GDP growth and real per capita income. While an effective two‐child policy could sustain growth and eventually mitigate the aged dependency problem, it would set real per capita income on a still lower path. These conundrums are examined using a global economic and demographic model, which shows how the continuing demographic and saving contractions in China would alter the trajectories of both the Chinese and global economies. [ABSTRACT FROM AUTHOR]

Based on 10342 Chinese family samples, by means of non-linear models, the effects of wage income tax (WIT), individual business income tax (IBIT) and other income tax (OIT) on the income gap in China are analyzed. It is found that China's classified income tax is helpful to narrow the income gap. WIT plays a very important role in narrowing the income gap, with IBIT and OIT widening the income gap. Such income taxes, especially WIT, cause differences of the tax burden between taxpayers who have the same income amount. Uniform income tax is an indispensable measure to solve the problems. On the basis of the income tax systems of 13 countries, 16 different kinds of personal or household uniform income tax modes were built up. Namibia's household uniform income tax mode is practical to China, because the income adjustment effect of such mode is stronger than that of China's classified income tax, but the average tax rate of it is lower than that of China's classified income tax. [ABSTRACT FROM AUTHOR]

The article constructs the VAR model, and empirically studies the interaction between per capita travel expenditure and disposable income of Chinese urban residents through impulse response function and variance decomposition method. The conclusion of the study shows that there is a long-term dynamic cointegration relationship between tourism expenditures and disposable income of urban residents in China, but the promotion between them is not enough. [ABSTRACT FROM AUTHOR]

Vehicle exhaust emissions are identified as one of the main determinants of air pollution and play an important role in the environmental sustainable improvement of countries. This research utilizes a panel data of 30 Chinese provinces during the period between 1997 and 2012 to examine the existence of inverted U-shaped relationship between public healthcare expenditure per capita and private car ownership across geographical regions (east, middle and west China) employing panel generalized method of moments estimates for robust estimates. The findings also show the income per capita significantly and positively impacts on health expenditure per capita at the national level. The other results indicate that sulfur dioxide emissions and people over age 65 significantly increase healthcare expenditure per capita except the western region; soot emissions have a significantly positive impact on public health expenditure per capita for only the whole country and the western region; the number of doctors per capita may decrease public health expenditure per capita caused by environmental pollution. These results have important policy implications for promotion of new energy vehicles and for improving air quality and medical and health services. [ABSTRACT FROM AUTHOR]

Energy security, as an indispensable constituent of economic security, has long been a top research priority, and the dynamics of energy security become particularly complicated with the involvement of climate change. In this work, we combined a one-sector integrated assessment framework with a series of well-proposed energy security metrics to extensively explore the unidirectional consistency between climate policy and energy security from the national perspective. Implementation of climate policy is generally beneficial for improving energy security. Specifically, climate policy helps to reduce the systematic risk of China's energy system according to the metrics of energy (oil) intensity, energy (oil) expenditures and per capita energy (oil) consumption independent of time scale options. As observed from the perspective of energy diversity, co-benefits arising from climate policy primarily emerge in the first half of this century, and they may gradually decline as emission constraints and the phasing out of fossil fuels are enhanced. Additionally, the macroeconomic costs required to reach China's committed carbon-peaking target might be far lower than the costs required to fulfill the emission budgets under the global 2-degree warming rise threshold. If the co-benefits of energy security are considered, the economics of climate policy is expected to significantly improve. [ABSTRACT FROM AUTHOR]

In recent years, along with rapid economic growth, China’s environmental problems have become increasingly prominent. At the same time, the level of China’s pollution has been growing rapidly, which has caused huge damages to the residents’ health. In this regard, the public health expenditure ballooned as the environmental quality deteriorated in China. In this study, the effect of environmental pollution on residents’ health expenditure is empirically investigated by employing the first-order difference generalized method of moments (GMM) method to control for potential endogeneity. Using a panel data of Chinese provinces for the period of 1998-2015, this study found that the environmental pollution (represented by SO2 and soot emissions) would indeed lead to the increase in the medical expenses of Chinese residents. At the current stage of economic development, an increase in SO2 and soot emissions per capita would push up the public health expenditure per capita significantly. The estimation results are quite robust for different types of regression specifications and different combinations of control variables. Some social and economic variables such as public services and education may also have remarkable influences on residential medical expenses through different channels. [ABSTRACT FROM AUTHOR]

This study focuses on China’s coastal area and its marine economic development. Applying the information diffusion method, the study establishes a kernel density function and its decomposition using a marine economic per capita as the index of the model to depict the dynamic evolution law and the internal influential factors of the Chinese marine economy during 1996-2013. The relative development rate was introduced to analyze the spatial differences in the marine economy’s development. In this way, space and time dimensions fully characterized the evolution of the Chinese marine economy. Additionally, the influence of growth and inequality in the process of its development can be analyzed. The study shows that the Chinese marine economy as a whole has been growing, and regional marine economic development is relatively coordinated. In addition, the marine economy began to develop even more rapidly after 2004. There are three factors affecting the dynamic evolution of China’s marine economy: first, the most influential mean effect, followed by, second, the variance effect, and third, the least influential residual effect. The biggest influence on the dynamic evolution of the marine economy is the improvement of the development level of the marine economy in the coastal area. Meanwhile, due to the existence of inequality, provinces at higher development levels are more dispersed. Furthermore, the existence of the residual effect weakens the influence of the mean effect, and the influence on the dynamic evolution of the marine economy continuously increases. In the analysis of the influencing factors of the evolution and spatial difference of marine economic development, the level of opening to the outside world, the level of investment in fixed assets and the industrial structure have a positive role in promoting economic development. However, capital investment in scientific human research has a negative correlation with economic development, and does not pass the significant test. The difference in regional development levels and development speed is also very apparent; namely, the provinces with higher development levels generally displayed faster development speeds while those with lower development levels showed slower development speeds across the four periods analyzed. [ABSTRACT FROM AUTHOR]

In this study, we investigate the driving forces behind the changes in residential energy consumption (REC) in China’s urban and rural areas over the 2001–2012 period. Based on the logarithmic mean Divisia index method, the REC changes are decomposed into seven driving forces, which are climate change, energy price, energy expenditure mix, energy cost share (in total expenditure), expenditure share (in income), per capita income and population effects. According to the results, climate effect due to increasing days with abnormal temperature, energy cost share effect characterized by more expenditure to be paid for energy use, income effect describing constant income growth in the residential sector definitely increase REC in both urban and rural areas. In contrast, energy prices and energy expenditure mix effects negatively contribute to the REC increase, respectively because of the increase in energy prices and the transition from the low-priced energy to high-priced energy. Expenditure share and population effects play opposite roles in urban and rural areas, and the reasons and implications are analysed in depth. [ABSTRACT FROM AUTHOR]

This paper proposes a new framework based on the combination of the dynamic DEA, meta-frontier analysis theory, and truncated regression model, and then focuses on the efficiency evaluation of regional high-tech industries in China. For all of the overall technical efficiency, technical efficiency, and scale efficiency scores, the east area is always in the lead, with the central and west areas obviously lagging behind. The eastern area has the highest technology level, whereas the west and central areas fall behind in turn. However, the meta-technology ratio of the west area has rapidly increased and presents a trend of catching up with the east. The variables of GRP per capital, total exports and imports, highway mileage per capita, and ratio of tertiary industry to GRP have positive relationships with technical efficiency, and the time trend exhibits a negative coefficient. [ABSTRACT FROM AUTHOR]

In recent decades, national income has become increasingly important as a measure of a nation's economic health. In this study, we used a wide array of primary and secondary sources to arrive at values of the Chinese per capita gross domestic product during the period of 1661-1933. We found a persistent decline in the per capita gross domestic product between the seventeenth and nineteenth centuries, followed by a period of stagnation. This pattern, which shows up in many Asian countries, with the exception of Japan, provides a basis for improving our understanding of the patterns of global economic convergence and divergence. [ABSTRACT FROM AUTHOR]

Urban household Electricity Consumption (UHEC) is receiving more and more attention in terms of energy saving and emission reduction. Currently, China lacks a mature methodology to explore the impacts and mechanisms of UHEC. This study selects physical characteristics, usage, and equipment factors associated with urban domestic dwellings to address these issues to develop an adequate theoretical model. The extended STIRPAT model was used to explore how each factor affects UHEC. Stepwise regression was then used to identify the mechanisms of influence between each factor and UHEC and to investigate the direct and mediating effects between floor area and UHEC. The results show that floor area, urbanization rate, the proportion of older people, per capita income, and unit energy consumption significantly contribute to UHEC. The direct effect of floor area on UHEC reaches 13.5%. GDP per capita and urbanization rate have a strong mediating role, at 47.8% and 28.1%, respectively, and the mediating contribution of unit energy consumption is 11.8%. A more novel factor, namely single-person households, shows a significant masking effect. In summary, this study is cutting-edge and provides a scientific decision and basis for developing household electricity-saving strategies in China and the world. • The extended STIRPAT model examines the effects of multiple factors on UHEC. • Mediation effects were used to identify mechanisms of influence between factors. • Significant provincial UHEC differences drive energy mix optimization. • Single-person households are a special variable presenting a masking effect. • Policy subsidies may mitigate the impact of aging and singlism on UHEC. [ABSTRACT FROM AUTHOR]

Household consumption has great potential to reduce CO 2 emissions from the demand side which is an important way to achieve carbon peaking and carbon neutrality goals. However, the shrinking household size will have a significant impact on household carbon emissions. In this paper, we have investigated the impacts of the decrease in Chinese household size on the direct and indirect household carbon emissions by using the input-output model and the bidirectional fixed-effect model, based on China's Urban Household Income and Expenditure Survey dataset. Results have shown that household size has a significant negative effect on household carbon emissions per capita, and such a negative effect on indirect carbon emissions is much greater than that on direct carbon emissions in China. Reducing the average household size by one has led to an increase of 0.128 t of the direct household carbon emissions per capita and 1.344 t of indirect household carbon emissions per capita, respectively. We also projected the potential change of household carbon emissions by 2030 under scenarios of increasing total population and shrinking household size and found that there may generate a 15.3%–18.8% growth in household carbon emissions compared to that in 2012, with other demographic characteristics unchanged. [ABSTRACT FROM AUTHOR]

With the increasing affluence, the differences in CO 2 emission between urban and rural residential sectors are remarkable and show an increasing trend. In case of China, residential sector accounts for a substantial share of the national CO 2 emission, bringing greater pressure to achieve the goal of carbon peak. Analyzing the emission inequality trend and its drivers is essential for formulating effective CO 2 emission reduction policies. However, the existing literature lacks relevant analysis from the viewpoint of urban-rural disparity. Hence, this study decomposes the CO 2 emission inequality of China's urban and rural residential consumption into four factors by combining the Theil index and Kaya decomposition. The results suggest that, in 2005–2020, the per capita CO 2 emission of rural residential consumption increased to a higher extent than those of urban households, with large differences in spatial distribution. Decomposition of the per capita CO 2 emission inequality for residential sector shows that the primary source is the inequality within the groups, mainly from the urban intra-group inequality. Based on the static decomposition, energy intensity appears as the main factor of urban–rural inequality. The dynamic decomposition shows that there have been differences in the factors of the change in the Theil index between urban and rural areas across sub-periods. • CO 2 emission inequality is discussed based on urban-rural differences. • A Kaya - Theil decomposition is developed. • The case of China is considered via static and dynamic decomposition. • The evolution and drivers of CO 2 emission inequality are explored. [ABSTRACT FROM AUTHOR]

China's fertility rate is below replacement level. The government is attempting to increase this rate by relaxing the one-child policy. China faces a possible tradeoff because further urbanization is needed to raise incomes but may reduce future fertility. We decompose China's rural-urban fertility gaps using both de facto and de jure criteria for defining the urban population. The fertility-depressing effects of holding urban hukou are more than three times larger than effects of urban residence. Less of the rural-urban fertility gap by hukou status is due to differences in characteristics than is the case for the fertility gap by place of residence. [ABSTRACT FROM AUTHOR]

Hundreds of studies in economics misinterpret China's subnational population and per capita data. The most widely used population counts are of hukou registrations from each province, prefecture, county, or city rather than of the people living in each place and generating local gross domestic product. Over 220 million people have left their place of registration, while almost none had when reforms began, creating time-varying errors in estimates of per capita income of subnational units. We survey empirical articles in blue ribbon journals, in development journals, and in regional and urban economics journals that use China's subnational data. Over 80% of articles use these data erroneously; most commonly the wrong population or employment counts are used to measure the size of subnational units, and per capita data are calculated with the wrong denominator for how variables are interpreted. We provide examples of errors from each group of journals, and a critical test of one highly cited study. Specifically, we show that if hukou registrations are erroneously used to measure the local population, following existing practice, conclusions about driving forces for urban area expansion are reversed. We give recommendations for more careful use of China's subnational population and per capita data. [ABSTRACT FROM AUTHOR]