Regional Differences In China Research Articles

Spatial-temporal Distribution of Aerosol Optical Depth and Its Main Influence Types in China During 1990-2017

In order to accurately understand the optical characteristics of aerosols in China, based on Mann-Kendall(MK) and Sen's slope trend analysis methods, the spatiotemporal variations of aerosol optical depth(AOD) derived from MERRA-2 reanalysis datasets were estimated in China for the period of 1990-2017. The results showed that ① for the interannual scale, there was a significant increasing trend in the annual mean AOD in China during 1990-2017. Besides, high aerosol loadings were observed in spring and summer, and the seasonal difference between the eastern and western regions was large. This was mainly due to the topographic and meteorological factors. ② At the spatial scale, the annual mean AOD values increased from the northwest to the southeast, with characteristically high AOD values occurring in Sichuan Pendi and the Tarim and Turpan basins and low values in the Qinghai-Xizang plateau region. Similarly, the AOD MK value and Sen's slope value showed significant decreasing trends from the southeast to the northwest, which was closely related to climate change and the human activity intensity. ③ In regard to black carbon aerosol, dust aerosol, organic carbon aerosol, sea salt aerosol, and SO4 aerosol, dust and SO4 aerosols were affected by the air humidity and human activity intensity, which have obvious regional differences in China.

Research on Optimization Allocation Scheme of Initial Carbon Emission Quota from the Perspective of Welfare Effect

The initial allocation of carbon emission quotas should be of primary concern when establishing China’s unified carbon emission trading market. Essentially, the issue of national carbon quota allocation is an allocation among China’s provinces. The novel bi-level allocation scheme that is based on weighted voting model is put forward, which divides allocation process into two levels, given that there are great regional differences in China. At the first level, k-means clustering is employed to cluster 29 provinces into four categories that are based on emission abatement responsibility, potential, capacity, pressure, and motivation. Subsequently, the national carbon quotas are allocated to the four classes. At the second level, carbon quotas of a class are allocated to each region in this class. The weighted voting models are constructed for the two levels, where each region selects their preferable scheme from three fundamental allocation schemes that are based on their voting rights. The comprehensive index method quantifies each region’s voting rights, which utilizes the information entropy method at the first level and the analytic hierarchy process (AHP) at the second level. The carbon trading market is simulated and welfare effects obtained from carbon trading market under different allocation schemes are measured to verify the rationality of the proposed model. The results indicate: (1) the emission abatement burdens are borne by all provinces in China, but the burden shares are different, which are related to their respective carbon emission characteristics. (2) The differences in carbon intensity among regions in 2030 have narrowed on the basis of the results of 2005, which means that the proposed scheme can balance corresponding differences. (3) When compared with three fundamental allocation schemes, the bi-level allocation scheme can obtain the most welfare effects, while the differences in the welfare effect among regions under this scheme are the smallest, which indicates that the proposed model is feasible for policy-maker.

Land Lease，Resource Misallocation and Total Factor Productivity

Since the reform and opening up, the Chinese economy has achieved rapid growth, accompanied by the gradual slowdown in the growth rate of total factor productivity. Compared with developed countries, China’s total factor productivity is still at a low level and there is a serious imbalance between regions. The rapid rise in house prices and land prices has made local governments’ development mode centered on land transfer, and it has been classified as the culprit” of high housing prices. What is worth exploring is: What impact does local governments’ development mode with land transfer as its core have on China’s total factor productivity? Can we explain the trend of change and regional differences in China’s total factor productivity from the perspective of land lease? This paper focuses on the impact of local governments’ land lease behavior on urban total factor productivity. Based on the existing research literature, this paper proposes two hypotheses of this study through the analysis of the status quo and the theoretical mechanism. On the empirical test, the SFA method is used to calculate the overall TFP of 230 prefecture-level and above cities. The instrument variable method tests the impact of local governments’ land lease behavior on the overall TFP of the city, and the adjustment effect of land price distortion on urban TFP under the horizontal subsidy” mode. At the same time, the matching data of the industrial enterprise database is used to verify the intermediate mechanism that the scale expansion of land lease income affects TFP. The main conclusions of the study are as follows: First, the expansion of land lease income significantly inhibits the total factor productivity of the city; local governments’ land fiscal expansion enhances the scale efficiency, but significantly inhibits the improvement of urban technology and technology allocation efficiency, and then has a hindrance to the total factor productivity of the city. Second, in the process of the expansion of land sale income, local governments tend to sell commercial land at high prices and transfer industrial land at low prices. The mode of horizontal subsidy” leads to land price distortion, and further aggravates the inhibition of total factor productivity by the expansion of land lease income. Third, the results of the mechanism test show that the excessive expansion of local governments’ land lease income leads to the resources misallocation” effect at the industry and city level, which in turn inhibits the total factor productivity of the city. The conclusions of the paper have important reference value for China’s land finance system reform and the total factor productivity improvement of the city. The marginal contributions of the paper mainly lie in three aspects: First, it enriches the existing research on total factor productivity from the perspective of local governments’ land lease. Second, it theoretically analyzes the impact of land lease behavior on urban total factor productivity. The intermediate mechanism reveals the resource misallocation” effect brought about by the excessive expansion of land lease income, and the overall efficiency loss caused by land price distortion under the local governments’ horizontal subsidy” mode. Third, the empirical study uses the instrumental variable method to solve the endogenous problems of local governments’ land lease behavior and economic activities.

Factors causing regional differences in China's residential CO2 emissions—evidence from provincial data

Residential energy consumption has increased sharply in China and is further expected to grow owing to rapid economic growth and improved living standards. The residential sector will be one of the leading drivers of greenhouse gas emissions. Therefore, this study divides China into three areas considering regional differences and re-investigates the influence of human activities on residential CO2 emissions in China's 28 provinces during 2000–2016. Using an extended stochastic impacts by regression on population, affluence, and technology model, the key factors behind residential CO2 emissions are investigated. The main findings are as follows: Residential CO2 emissions in China have regional characteristics and the effects of urbanization, energy intensity, and price elasticities vary among the three regions. GDP per capita is the key factor and positively influences total residential CO2 emissions. By adding the squared and cubed terms of GDP per capita, the environmental Kuznets curve hypothesis is tested for all regions and for China overall. The results confirm the environmental Kuznets curve in the eastern region and show an “N” shaped curve at the national level.

Analysis of the influencing factors on CO2 emissions at different urbanization levels: regional difference in China based on panel estimation

A large amount of carbon dioxide emissions have drawn more and more attention recently. Existing regional research is mainly based on the classification of geographical location, without considering the differences in urbanization. Using panel data of 30 provinces in China during the period of 1997–2014, this paper investigates the impact of population, per capita GDP, energy intensity, urbanization, industry proportion and tertiary industry proportion on CO2 emissions. Taking into account regional differences, 30 provinces in China are divided into four regions according to the features of “urbanization–CO2 emissions.” The results show that the impacts of population and per capita GDP on CO2 emissions in the LU–LC region are higher than the other three regions. The energy intensity has positive effect on CO2 emissions in the four regions. The impact of energy intensity on CO2 emissions in HU–HC and HU–LC regions is greater than the other two regions. Meanwhile, the impact of urbanization on CO2 emissions differs across regions. The urbanization has a significant negative effect on CO2 emissions in the HU–LC region, indicating the urbanization increases CO2 emissions. However, the urbanization has a positive effect on CO2 emissions in the LU–HC region, indicating the urbanization increases CO2 emissions in the region. The impact of industry proportion is not statistically significant in all the regions, while the impact of tertiary industry proportion on CO2 emissions is negatively significant in the HU–LC and LU–HC regions, which indicates that the adjustment and upgrading of industrial structure play important roles in the decrease in carbon emissions.

Regional Comparisons of Contemporary Construction Industry Sustainable Concepts in the Chinese Context

Emerging construction practices such as building information modelling (BIM), prefabrication construction, green building, and integrated project delivery methods are gaining momentum in China, with great potential due to the size of its construction market. Through this, the sustainability level of China’s construction industry is expected to be enhanced from the economic, social and environmental perspectives. So far, there has been limited understanding of how BIM, as a digital technology, would affect other contemporary sustainable construction practices from the industry professionals’ point of view. Limited studies have been carried out to study the regional differences of these contemporary sustainable practices in China. This study adopted a questionnaire-based approach targeting industry professionals from three different metropolitan cities (Shanghai, Guangzhou, and Wenzhou).The follow-up comprehensive statistical analysis revealed that with regards to these contemporary sustainable construction practices, survey participants held much varied views on the growth of renovation projects, traditional Design–Bid–Build delivery, and conventional on-site construction methods. These three types were also generally perceived to have weak correlation with BIM application. Regional comparison further conveyed information on differences in perceptions among survey respondents from these three cities. For example, respondents from Wenzhou perceived more positive effects of BIM use in conventional construction projects. This research addressed the inter-correlation among these emerging sustainable construction practices, as well as the regional differences in China’s construction market. The findings provide insights and the big picture for both governmental authorities and industry practitioners on the latest sustainable practices of China’s construction industry. Recommendations are also offered towards improved economic, social and environmental sustainability performance for construction projects in the country.

Study on Gasoline Vehicle Emission Inventory Considering Regional Differences in China

Rapid growth of China’s urban road vehicles, in particular, the increase in the number of gasoline vehicles, leads to an increase in the traffic congestion and problems pertaining to air pollution. The establishment of the emission inventory of gasoline vehicles is influenced by several factors, like environmental characteristics, vehicle conditions, road conditions, and so on. In order to obtain gasoline vehicle emission inventory in accordance with the actual situation in different regions, this study proposed a method of establishing a list of gasoline vehicles with regional differences. Comprehensive consideration and evaluation of various factors that affect the vehicle emissions were carried out and the corresponding correction factors were obtained. According to the formula of comprehensive emission factor for Zibo city, the emission inventory of gasoline vehicle was established. This method can be effectively utilized to obtain the emission inventory of gasoline vehicles in different cities more accurately and provide theoretical support for control strategies of gasoline vehicle emissions.

Bi-level allocation of carbon emission permits based on clustering analysis and weighted voting: A case study in China

A rational regional allocation scheme of carbon emission permits is important for establishing the nationwide carbon emission trading system (ETS) of China. Considering the vast area and great regional differences in China, a novel bi-level allocation scheme based on clustering analysis and a weighted voting model is proposed in this research. At the first level, 30 regions in China are clustered into four classes according to their characteristics of carbon emissions, which include emission reduction pressure, capacity, responsibility and potential. Then the total carbon emission permits are allocated to each class of regions. At the second level, carbon emission permits are allocated to each province (municipality) within a class. The weighted voting models are developed for both the two levels, where the allocation schemes based on historical emissions, population and GDP are selected by each region according to the different voting rights of each region. The voting rights of each region for choosing its inclined scheme are quantified through a multi-index comprehensive evaluation, which employs the entropy method at the first level due to the lack of prior knowledge and the analytic hierarchy process (AHP) at the second level to increase policy flexibility. The combination of subjective weighting evaluation method (AHP) and objective weighting evaluation method (the entropy method) increases the flexibility of the abatement policy while guaranteeing the objectivity of decision-making process. Case studies of the allocation for carbon emission permits in China by 2020 and 2030 are carried out under the proposed allocation scheme. The derived allocation results show that the proposed allocation scheme can provide a balanced consideration to equality and efficiency, which are compared with those in reported literatures. The proposed allocation scheme can not only encourage all regions to reduce carbon emission intensity, but also achieve in meeting the carbon emission demand of the population in each region.

Influence factor analysis of migrants' settlement intention: Considering the characteristic of city

The settlement intention of migrants is an important factor for urban development. Through examination of existing research we found that the influencing factors on settlement intention differed by region; however, little attention was paid to the factors affecting settlement intention based on regional differences in China. Using data from the National Health and Family Planning Commission of the People's Republic of China, this study chose 282 cities as study areas, First, this was performed through the statistic and spatial analysis of GIS, which explains the effect of the city level variable on settlement intention; then, it introduced a hierarchical linear regression model, combining macro statistics with micro-survey data to explain the factors influencing settlement intention as well as the relationship between the city-level variable and the individual-level variable. The results showed three things: First, the characteristic of city had an impact on the settlement intention. Second, the regional difference of settlement intention was significant, it was interesting insofar as Eastern China attracted the most migrants but the settlement willingness of migrants in the east was the most insignificant. Thirdly considering the characteristic of city, education, age, income, employment status and occupation type had a significant effect on urban settlement intention.

Performance evaluation of China's high-tech innovation process: Analysis based on the innovation value chain

The Chinese high-tech industry has developed greatly since the beginning of China's “National High-tech R&D (863) Program” and “China Torch Program”. This paper introduces a conceptual model extended from the innovation value chain model to simultaneously estimate the R&D and commercialization efficiencies for the high-tech industries of 29 provincial-level regions in China. To match reality, a network DEA incorporating both shared inputs and additional intermediate inputs is constructed to open the “black box” view of decision making units used in single-stage DEA. This study is the first attempt to link the R&D and commercialization with a solid theoretical foundation and feasible mathematical methods. The empirical findings show that most of the 29 regions have low efficiency in the commercialization sub-process compared to the R&D sub-process, although there are regional differences in China's high-tech industry. Pearson correlation shows that the R&D sub-process is not closely correlated to the commercialization sub-process in terms of efficiency. Our analysis can provide information for the formulation of policies to achieve high innovation efficiency.

Hazard regionalization of debris-flow disasters along highways in China

Regional differences in China’s natural landscape involve significant differences in the distributions of debris-flow disasters along highways (DFDHs), which makes it very difficult to forecast, identify, and provide early warnings for such disasters. Previous research mainly focused on single-gully debris-flow disasters or a number of debris-flow disasters with similar morphological characteristics, which could not reflect the inherent mechanisms leading to the occurrence of DFDHs. Hazard regionalization of DFDHs in China can clarify the priorities and protection standards for different areas in China, and provide a theoretical basis for macro-policy formulation. We identify the hazard sources of DFDHs, extract hazard assessment indicators, and calculate the weight of each indicator using a cloud model-improved analytic hierarchy process. We draw basic maps of assessment indicators and perform a spatial analysis of hazard of DFDHs using ArcGIS, and a hazard regionalization scheme for DFDHs in China is developed. The results show that the degree of hazard of DFDHs in China ranges from 1.000 to 7.900. China is divided into low, moderate, severe, and extremely severe hazard areas. The extremely severe hazard areas are the Loess Plateau (north part of the QinBa Mountain area), the Taiwan–Wuyi Mountain area, the Sichuan–Yunnan Mountain area, and the Tianshan–Kunlun Mountain area.

Regional differences of urbanization in China and its driving factors

After more than 30 years of rapid urbanization, the overall urbanization rate of China reached 56.1% in 2015. However, despite China’s rapid increase in its overall rate of urbanization, clear regional differences can be observed. Furthermore, inadequate research has been devoted to in-depth exploration of the regional differences in China’s urbanization from a national perspective, as well as the internal factors that drive these differences. Using prefecture-level administrative units in China as the main research subject, this study illustrates the regional differences in urbanization by categorizing the divisions into four types based on their urbanization ratio and speed (high level: low speed; high level: high speed; low level: high speed; and low level: low speed). Next, we selected seven economic and geographic indicators and applied an ordered logit model to explore the driving factors of the regional differences in urbanization. A multiple linear regression model was then adopted to analyze the different impacts of these driving factors on regions with different urbanization types. The results showed that the regional differences in urbanization were significantly correlated to per capita GDP, industry location quotients, urban-rural income ratio, and time distance to major centers. In addition, with each type of urbanization, these factors were found to have a different driving effect. Specifically, the driving effect of per capita GDP and industry location quotients presented a marginally decreasing trend, while main road density appeared to have a more significant impact on cities with lower urbanization rates.

Investigating the role of high-tech industry in reducing China's CO2 emissions: A regional perspective

China currently is the largest emitter of carbon dioxide (CO2) in the world. Moreover, total energy consumption and CO2 emissions in China will continue to increase due to the rapid advance of industrialization and urbanization. Therefore, vigorously developing the high–tech industry becomes an inevitable choice to reduce CO2 emissions at the moment or in the future. However, most of the existing literature analyzes the impact of the high–tech industry on emission mitigation from an aggregate perspective. Few studies have focused on regional differences in China. Based on 1999–2015 panel data of China's 30 provinces, this study uses the STIRPAT model to explore the influence of the high–tech industry on CO2 emission reduction in China from a regional perspective. The results show that the high–tech industry is beneficial to reduce CO2 emissions. Moreover, the impact intensity of the high–tech industry in the eastern region is higher than those in the central and western regions due to significant differences in R&D funding, R&D personnel investments and high–tech purchase expenditure. The study's findings not only contribute to the existing literature, but also worthy of adequate attention from China's policy makers.

Higher Education Development and Regional Differences in China

This paper analyzed the development of higher education and the regional differences in China, using the survey data and official statistics. Two indicators, the undergraduate students of per 100,000 population and higher education’s contribution to GDP growth, were applied respectively to study the regional differences. The results showed that higher education in China was enjoying great development, fundamentally constructed talent cultivation system and comprehensively reasonable resource distribution. However, some colleges and universities still had some problems, such as incorrect orientation, overheated scale expansion and insufficient capital investment. Besides, higher education in China was suffering from considerable regional differences, namely higher education in East China is developing rapidly and contributing more to the economic growth, while the West China has presented slower rate of higher education development and smaller contribution to economic growth. Based on the problems lying in present reality of higher education development, this paper proposed the suggestions to enhance the development of higher education in China and to dispel the regional differences in higher education performance.

The impact of corporate social responsibility on customer loyalty: A case for two global corporations in China

AbstractCorporate social responsibility (CSR) initiatives have differential impact on developing customer loyalty in the context of two leading international sportswear companies operating in China. Academic interest in CSR in China has grown over the years. The findings suggest a relatively strong impact of CSR dimensions (e.g., workplace, marketplace, and environment support) and other related attributes (e.g., price, product quality, and uniqueness) on developing customer loyalty in China. There are regional differences in China in relation to customers’ CSR perceptions and the likelihood of being influenced by a company’s CSR initiatives.

Regional disparities in China's marine economy

Understanding the performance of each coastal area as it develops is the primary task of policy-makers in a marine economy; however, quantitative regional differences in China's marine economy have not been empirically examined. This paper offers a methodological contribution by applying a series of techniques, including the variation coefficient, Gini coefficient, and Theil index decomposition, to illustrate the relative differences among coastal areas. Additionally, the coastal areas of China were divided into two categories to reveal the provincial differences and regional disparities in China's marine economy. The results show that although the numerical economic differences in Gross Ocean Product (GOP) among coastal areas have increased significantly during the 21st century, the gaps among coastal regions have gradually decreased. In addition, China's marine economy presents three levels of regional development (developed, medium-developed, and developing). The results of the Theil index decomposition show that the overall difference in China's marine economy is derived mainly from differences within the three macro marine economic regions; these differences account for more than 95% of the overall difference. Furthermore, the underlying reasons for and driving mechanism of regional differences in China's marine economy can be illuminated in terms of differences in natural resource endowments and geographic locations; industrial agglomeration and diffusion; changes in regional development policy; and foreign investment. These findings offer basic data support and policy recommendations for marine economy management at the national and regional levels.

Does the high–tech industry consistently reduce CO2 emissions? Results from nonparametric additive regression model

China is currently the world's largest carbon dioxide (CO2) emitter. Moreover, total energy consumption and CO2 emissions in China will continue to increase due to the rapid growth of industrialization and urbanization. Therefore, vigorously developing the high–tech industry becomes an inevitable choice to reduce CO2 emissions at the moment or in the future. However, ignoring the existing nonlinear links between economic variables, most scholars use traditional linear models to explore the impact of the high–tech industry on CO2 emissions from an aggregate perspective. Few studies have focused on nonlinear relationships and regional differences in China. Based on panel data of 1998–2014, this study uses the nonparametric additive regression model to explore the nonlinear effect of the high–tech industry from a regional perspective. The estimated results show that the residual sum of squares (SSR) of the nonparametric additive regression model in the eastern, central and western regions are 0.693, 0.054 and 0.085 respectively, which are much less those that of the traditional linear regression model (3.158, 4.227 and 7.196). This verifies that the nonparametric additive regression model has a better fitting effect. Specifically, the high–tech industry produces an inverted “U–shaped” nonlinear impact on CO2 emissions in the eastern region, but a positive “U–shaped” nonlinear effect in the central and western regions. Therefore, the nonlinear impact of the high–tech industry on CO2 emissions in the three regions should be given adequate attention in developing effective abatement policies.

Impact of urbanization on energy related CO2 emission at different development levels: Regional difference in China based on panel estimation

We examined the influence of urbanization on CO2 emission at different development levels employing the stochastic impacts by regression on population, affluence and technology (STIRPAT) model on provincial panel data from 1995 to 2013 for China. To investigate regional differences based on development levels in the effects of urbanization on CO2 emission, we divided the 29 provinces of China into three regions according to their per capita real GDP at constant value (1990 = 100). The panel estimation for the whole dataset and the three regions showed an inverted U relationship between urbanization and CO2 emission in the major regions of China. Specifically, the effects of urbanization vary significantly across the regions. In region 2 and region 3, a threshold level was identified, beyond which the emission urbanization elasticity was negative, and further increases in the urbanization rate did not contribute to higher emissions. However, in region 1, only population and affluence, rather than urbanization, were significant factors affecting CO2 emissions. In addition, the results did not confirm the environmental Kuznets Curve relationship between income and CO2 emission, where CO2 emission increases monotonically with income. We propose a series of policy implications based on these outcomes to help realize emission reduction targets better.

Regional differences in China's fossil energy consumption: an analysis for the period 1997–2013

Measuring regional differences in fossil energy consumption is the first step to the study of natural resource allocation and utilization. This paper employs annual and cumulative consumption Gini indexes as well as the deviation index to discuss regional differences in the per capita consumption of fossil energy and related products across 30 Chinese provinces from 1997 to 2013. The results show that Chinese inter-provincial Gini ratio of fossil energy consumption is below 0.3 in recent years, and change in per capita energy consumption is the key factor behind the decline in the overall Gini index. Unlike existing studies based only on annual flows of energy consumption, this paper also focuses on cumulative energy consumption. Moreover, decomposing annual and cumulative consumption Gini coefficients by type, group, and incremental variation is rarely seen in other studies. Based on the above positive analysis, the paper provides some policymaking suggestions.

Contextual Effect of Wealth on Independence: An Examination through Regional Differences in China.

The current study disentangled two different effects of wealth on psychological tendency toward independence: one is an effect exerted at the individual level (i.e., being rich) and the other one is a contextual effect (i.e., being surrounded by rich individuals). Past research has found a stronger tendency toward independence among people in economically developed societies. This association has often been explained as a result of a greater amount of choices, and thus more opportunities to express individuality that wealth affords individuals. In addition to this individual-level process, theories in cultural psychology imply that the wealth-independence link also reflects social processes—living in a rich society, regardless of one’s own wealth, promotes independence (contextual effect of wealth on independence). Through a large-scale survey in China, using multilevel analyses, we found that wealth had both the individual-level effect and contextual effect on independence as well as related psychological tendencies (influence orientation and generalized trust), suggesting that individuals are more likely to be independent with greater personal wealth and when surrounded by wealthy others. Possible processes through which independence is promoted by liing in a wealthy area are discussed.