Convergence In China Research Articles

The impact of innovative human capital on green growth convergence in China's regions from the perspective of space

The convergence of green growth is not only very important for the sustainable development of mankind, but also plays a key role in the coordinated development of eastern, Midwest regions of China. The effect of innovative human capital (IHC) on the convergence of regional green growth in China needs to be explored. This paper empirically explores the impact of IHC on the convergence of regional green growth in China from spatial perspective for the first time. Through the regression analysis of the convergence models, three main conclusions are obtained: (1) there are obvious conditional β space convergence characteristics of green growth among inter-provincial units in China. Under the spatial correlation expressed by distance weights and adjacent weights, the conditional β space convergence characteristics of green growth are quite different. (2) Compared with the adjacency weight, under the distance weight, the spatial diffusion effect of innovative knowledge and technologies created by IHC is stronger. (3) There is club convergence of green growth in the East and the Midwest regions, and the quantity and quality of IHC in the Midwest region play a stronger role in the convergence of green growth than in the East region. Based on the above conclusions, this paper proposes some policies for the East and Midwest regions.

Analyzing the Communication of Poverty Governance: A Study of Multimodal News Framing and Engagement on Chinese TikTok

Poverty communication is a critical yet challenging aspect of promoting sustainable development goals (SDGs) globally. This study explores poverty-related news narratives on Douyin (China’s TikTok) and examines their impact on user engagement (likes, shares, and comments). The primary objective is to refine communication strategies aimed at alleviating poverty. Drawing primarily on the news framing theory, this study analyzes 400 short-video news from Douyin in 2020 through regression analysis, complemented by insights from Chinese mobile news practitioners. Findings suggest that episodic-gain coverage, which emphasizes real-life scenarios and individual determination, effectively engages users. Visual framing devices, including action-driven and speech-driven opening scenes, captivate viewers and mobilize social support. Additionally, this study reveals that storytelling redundancy enhances news engagement by improving perceptual fluency in short videos. Moreover, tailored rhetorical strategies for short videos, such as subjective expressions and question-based headlines, further evoke the exchange of users’ social values. In conclusion, Douyin plays a central role in the ongoing process of media convergence in China. The study explores how platforms such as Douyin can promote SDGs, encourage public participation in addressing poverty and social care, and provide valuable insights for news content creators seeking to enhance storytelling and engagement in mobile media.

Capital deepening and land average grain yield convergence: Evidence from China

The shift of agricultural labor force to non-agricultural sectors has paralleled China's economic development, leading to a substantial rise in labor costs relative to capital. Consequently, the agricultural production has witnessed a shift towards capital-intensive practices. The capital deepening coincides with the significant increase in China's grain output while the main cause of capital deepening in China's grain production is poorly understood. This study examines the effect of increasing in various capital investments on the grain yield growth and growth convergence in China's main production areas, based on the data collected from the data set of the Compilation of Cost-Benefit Data of Agricultural Products (CCBDAP). Results show that the increases of chemical fertilizer, pesticide and machinery input have played key roles in the increase of grain yield. For early indica rice, japonica rice, wheat and maize, the average land output bears a β convergence. These findings suggest that more capital investments are supposed to accelerate the growth of grain yield per unit of land, take the opportunity of practicing the cross-provincial balance system of occupation and compensation of cultivated land. Moreover, strategic adjustments to the spatial distribution of grain cultivation are recommended to maximize the utilization of limited arable land resources while upholding national food security objectives.

From pixels to prosperity: does the digital economy reinforce or mitigate urban economic convergence in China?

ABSTRACT In an era where the digital economy is reshaping global economic landscapes, its impact on urban economic convergence remains a subject of considerable debate. This study delves into the intricate relationship between the digital economy and urban economic convergence across 337 prefecture-level cities in China from 2006 to 2020, a critical area of research given the country’s rapid digitalization and urban development. Using the β-convergence model, our findings reveal a general trend of economic convergence among cities, with the digital economy both facilitating and hindering this process. In addition, the impact of the digital economy on urban economic convergence is found to be heterogeneous, significantly influenced by the levels of human and physical capital and the extent of digitalization within cities. This heterogeneity underscores the presence of a ‘digital divide’, where the benefits and challenges of digitalization are not uniformly experienced across urban centres. Conclusively, we recommend targeted policy interventions to bridge the digital divide, enhancing digital literacy, and developing digital infrastructure in underdeveloped urban regions. Such targeted measures are essential for ensuring that the digital economy serves as a catalyst for equitable and sustainable urban development across China’s diverse urban landscape.

A Study on the Distribution Dynamics, Regional Disparities, and Convergence of China’s Energy Transition

Energy transition, as a crucial aspect of the country’s high-value-added economic development, involves the construction of an energy transition index system and empirical analysis using methods such as the entropy weighting method, kernel density estimation, Markov chain, Dagum Gini coefficient, σ-convergence, and β-convergence. This study measures the level of energy transition in 280 Chinese cities from 2010 to 2019 and analyzes their evolutionary trends, regional disparities, structural differences, and convergence. The findings reveal that China’s energy transition generally exhibits characteristics of “improvement in development levels and reduction in absolute disparities”. The disparities in energy transition primarily stem from developmental differences among the three major regions, displaying typical σ-convergence and β-convergence characteristics. This analysis contributes to understanding the real level and distribution features of China’s energy transition, providing a basis for identifying focal points for enhancing energy transition in the current and future stages.

Spatio-temporal pattern and the evolution of the distributional dynamics of county-level agricultural economic resilience in China.

Because the complexity of the external environment has put great pressure on the agricultural economy, making it vulnerable, it is necessary to promote a system of resilience in the agricultural economy so that Chinese agriculture can continue to persevere in the face of serious external uncertainties. Therefore, this paper investigates the spatio-temporal pattern and evolution of the distributional dynamics of China's county-level agricultural economic resilience based on 2000-2020 data covering 2,545 counties. The results are as follows: first, from 2000 to 2020, the mean value of China's county-level agricultural economic resilience showed an obvious upward trend, which indicates that China's agricultural economy gradually increased its ability to resist risks and continued to develop in a favourable manner. Specifically, the county-level agricultural economic resilience index of the northeast region grew the most significantly, while the index of county units in the western region was relatively low. Second, the centre of gravity of the spatial distribution of China's agricultural economic resilience gradually migrated to the northwest, showing a dominant direction from northeast to southwest and a tendency to develop from southeast to northwest. Third, the spatial differences in China's agricultural economic resilience generally showed an upward trend, while county-level differences were the main source of the overall differences, followed by inter-provincial differences, inter-municipal differences and inter-regional differences. Additionally, the contribution of county-level differences to the overall differences fluctuated within the range of 54%-58%. Fourth, there is a possibility of localized convergence in China's agricultural economic resilience, which is continuous in spatial effects and has obvious positively correlated spatial effects at different times and in different county spaces.

Building Bridges or Walls? Understanding Urban-Rural Price Convergence in China

Building Bridges or Walls? Understanding Urban-Rural Price Convergence in China

THE DIFFERENTIAL EFFECTS OF CREDIT POLICY ON REAL ESTATE PRICES FROM THE PERSPECTIVE OF CLUB CONVERGENCE

This study investigates the differential effects of credit policy in the context of real estate price convergence in China. First, we analyze the real estate price convergence of 35 large and medium-sized cities in China using [Formula: see text] convergence and club convergence methods. Subsequently, based on the convergence situation, we use panel models to compare the heterogeneous effects of the credit policy regulation of different clubs. The findings are as follows. (1) In terms of overall convergence, the findings confirm that there is no [Formula: see text] convergence in China’s real estate prices. Prices in each city do not show a trend of convergence to the total mean. (2) There are currently four convergence clubs and one divergence group in terms of regional convergence. Cities with similar initial price levels have similar structural characteristics and tend to converge to their respective local steady states. GDP per capita and population density are the main driving forces for the formation of a real estate price convergence club. (3) We show that the credit scale has a statistically positive impact on the real estate price, and the credit scales of various convergence clubs have different effects on real estate prices. Clubs with more developed real estate and financial markets are more sensitive to changes in credit policy.

Analysis of the impact of managers' psychological deviation on information disclosure and irrational overseas investment after IFRS convergence

Based on a sample of 6485 firms listed on the Chinese Shanghai and Shenzhen A-shares between 2017 and 2021, the effect of managers' psychological deviation on irrational investment is empirically tested. The higher the managers’ confidence, the lower the investment efficiency. The level of irrational investment in listed companies increases with the degree of managers’ risk appetite. The improvement of disclosure quality of enterprises after IFRS convergence in China can weaken irrational investment triggered by managers' overconfidence. The information disclosure quality by companies can manage the irrational investment behavior that is exacerbated by the high degree of managers’ risk appetite.

Characteristics and Influencing Factors of Provincial Industrial Convergence Networks in China

Abstract The 20th National Congress of the Communist Party of China proposed accelerating the promotion of Chinese-style modernization, placing higher requirements on regional economic development. In this context, interregional industrial convergence has become a new driving force for achieving high-quality economic development and regional industrial transformation and upgrading. Using the 2017 interregional input-output table provided by Carbon Emission Accounts and Datasets (CEADs), this study constructs a directed weighted network from both the supply side and the demand side, with “province-industry” as the node and the real flow between industries as the edge weight. Network analysis is used to investigate the overall status of industrial convergence in China, as well as differences according to industry and region. Finally, an exponential random graph model (ERGM) is used to examine the influencing factors and effects of network formation. The results show the following: (1) the industrial convergence relationship between regions in China is transitive and reciprocal, and the overall tendency of the network is one in which output capacity is greater than absorption capacity. (2) The marginal flow of manufacturing and services occupies an absolute advantage in China’s industrial convergence network, in which mid-end manufacturing and producer services are the most prominent. (3) Industrial convergence between provinces has formed a hierarchical spatial layout of “output-conduction-absorption”. In the absorption layer, the breadth and depth of Beijing’s industrial integration are characterized by absorption-dominant development. In the output layer, Shanghai’s capital-intensive industries have a strong external radiation capacity and generally show open-led development. (4) Interregional industrial convergence tends to occur in areas with similar economic levels and output value levels, showing a coordinated development trend of high-level output and low-level absorption, which is also affected by location proximity relationships, regional technology gaps, and employment population gaps. This research shows that China’s inter-provincial industrial convergence network generally shows the characteristics of spatial hierarchy, significant industry differences and multi-factor drivers.

Aggregation and the New News Order: A Practice Theory Approach

This study examines the transforming power of aggregation in a traditional newsroom based on the practice theory approach. Through ethnographic observations of aggregated news production in action in a local legacy press, we were able to detect various symbolic and material sources of institutional change attributable to aggregation. Some of our findings confirmed the prescriptions of practice theory; some extended it; and some partially negated the existing model due largely to the lack of a goodness-of-fit between the Western theory and the unique Chinese media ecology. We found that a new news order has emerged at the expense of professional quality of journalism, causing massive depletions of resources traditionally reserved for news beats, background research, maintaining the network of news contacts, and depth investigation. As a concrete practice of the highly politicized campaign for media convergence in China, aggregation is re-defining news making, practitioner identity and the cultural authority of journalism. Theoretical implications of this research are discussed.

Evaluation of coupling coordination development between digital economy and green finance: Evidence from 30 provinces in China.

The convergence of China's digital economy and green finance holds great significance for fostering a sustainable and high-quality developmental path. However, existing studies have not explored the coupling coordination development between these two crucial subsystems. To bridge this gap, this paper employs a modified coupling coordination degree (CCD) model to assess and affirm the coupling coordination degree between the digital economy and green finance across 30 provinces in China from 2015-2021. Based on degree results, provinces are classified into three clusters by using K-means and hierarchical clustering algorithm. Our findings unveil that the current level of coupling coordination development in China is at a primary coordination stage. Although regional disparities significantly exist, the overall level of coordination remains steadily increasing, with the eastern region outperforming the western region. Additionally, we determine that the COVID-19 pandemic's disruption on the coupling coordination development of these systems has been limited. This research sheds light on the evolution of coupling systems and offers practical recommendations for strengthening the coordinated development of the digital economy and green finance.

How Entrepreneurial Self-Efficacy Promotes Part-Time Entrepreneurial Behavior: The Moderating Role of Entrepreneurial Resources

With the convergence of China’s “entrepreneurial society” and the “digital age,” part-time entrepreneurial behavior (PEB) has received widespread attention as a new form of labor relations and entrepreneurial paths. Entrepreneurial self-efficacy (ESE) is an important indicator of entrepreneurs’ confidence in their skills and in coping with uncertain entrepreneurial challenges. However, studies on how ESE affects different types of PEB have not been thoroughly carried out. To fill the existing research gap, the primary objective of this paper is to thoroughly investigate the individual impact of three key factors, namely organizational management self-efficacy (OMSE), opportunity development self-efficacy (ODSE), and risk-taking self-efficacy (RTSE), on economic profit-driven part-time entrepreneurial behavior (EPEB) and self-value-driven part-time entrepreneurial behavior (SPEB), respectively. Based on the “cognition-environment-behavior” logic of triadic reciprocal determinism, this study also aims to examine the moderating effect of entrepreneurial resources (ERs) and attempt to understand how external factors regulate internal factors (OMSE, ODSE, and RTSE) to form the results of EPEB and SPEB. This study adopted a quantitative research approach with a questionnaire survey, taking 457 part-time entrepreneurs in 11 major cities as subjects. The main results show that (1) OMSE and ODSE have a positive effect on EPEB, while RTSE has an inverted U-shaped effect on it; (2) ODSE and RTSE have a positive effect on SPEB, and OMSE has an inverted U-shaped effect on it; and (3) ERs play a positive moderating role in the above processes. The results can not only effectively guide part-time entrepreneurs in PEB but also provide a reference for the government to improve part-time entrepreneurship policies.

Regional Differences, Distribution Dynamics, and Convergence of the Green Total Factor Productivity of China’s Cities under the Dual Carbon Targets

Economic development in China has been severely restricted by environmental problems such as carbon emissions. Improving green total factor productivity (GTFP) is an extremely important pathway to realizing carbon peak and carbon neutrality. Nevertheless, existing studies on China’s urban GTFP under the carbon emissions constraint are still insufficient. In this context, this study adopts the directional distance function (DDF), includes carbon emissions in the undesirable output, combines the global Malmquist–Luenberger (GML) productivity index, and calculates the GTFP of China’s cities. On this basis, the Dagum Gini coefficient, kernel density estimation, and convergence model are employed to explore the regional differences, distribution dynamics, and convergence in China and in three subdivision regions of east, center, and west. The core conclusions are as follows: (1) the average annual growth rate of GTFP in China’s cities is about 0.7064%, which is relatively low, but there is great room for improvement. The growth trend of GTFP in the three subdivision regions of east, center and west is obvious, presenting a spatial distribution characteristic of “high in the east and low in the west”; (2) the regional differences in GTFP of these cities are enlarging, with the largest gap in the eastern region and the smallest in the western region. Intraregional difference is the primary source of regional differences; (3) the imbalance in urban GTFP in China is prominent, with noticeable gradient differences, making it difficult to achieve hierarchical crossing. The central and western regions even have multilevel differentiation problems; (4) there is an absolute β convergence and conditional β convergence of China’s GTFP, but no σ convergence. As a result, it is necessary to comprehensively consider and actively implement the concept of shared development, enhance technological progress, focus on narrowing the differences in GTFP, and facilitate coordinated green development within the regions.

Measurements and spatio-temporal evolution of regional energy efficiency convergence in China

Balancing the ecological and economic benefits of energy consumption is an essential requirement and a key part of achieving the task of high-quality economic development and the goal of carbon neutrality. This paper analyses the energy efficiency and spatial and temporal evolution characteristics of thirty Chinese provinces and cities from 2006 to 2019 based on the DSBM model. The results show that, firstly, environmental factors have a significant impact on the evaluation of energy efficiency, with the national energy efficiency showing phase fluctuations and a decreasing trend from the east to the center and then to the west during the sample period. Secondly, the country and the three major regions did not show a σ convergence. Thirdly, there is significant absolute and conditional convergence in overall energy efficiency after considering spatial spillover effects, and with a turning point. Fourthly, energy efficiency in the three major regions also shows a clubbing phenomenon, with different regions tending to their own steady state of energy efficiency. Finally, we put forward suggestions for improving energy efficiency. The results of the study help to understand the changing trends and influencing factors of inter-regional energy efficiency in China, which can provide a reference for achieving the transformation of energy structure and has important practical significance.

Regional Differences, Dynamic Evolution and Convergence of Public Health Level in China.

People's health is a necessary condition for the country's prosperity. Under the background of the COVID-19 pandemic and frequent natural disasters, exploring the spatial and temporal distribution, regional differences and convergence of China's provincial public health level is of great significance to promoting the coordinated development of China's regional public health and achieving the strategic goal of a "healthy China". Based on China's provincial panel data from 2009 to 2020, this paper constructs an evaluation index system for China's public health level from five dimensions: the popularization of a healthy life, optimization of health services, improvement of health insurance, construction of a healthy environment, and development of a health industry. In this paper, the entropy method, Dagum Gini coefficient, Kernel density function and spatial econometric model are used to analyze the spatiotemporal distribution, regional differences, dynamic evolution and convergence of China's public health level since the new medical reform. The study found that, first, China's public health level is generally low, structural contradictions are prominent and the construction of a healthy environment has become a shortcoming hindering the improvement of China's public health level since the new medical reform. The public health level of the four major regions showed a spatial distribution pattern of "high in the eastern, low in the northeastern, central and western" areas. Second, the overall Gini coefficient of China's public health level showed a "V-shaped" trend of first decreasing and then rising, but the overall decrease was greater than the increase, among which the regional difference was the main source of regional differences in China's public health level, but its contribution rate showed a downward trend. Third, except for the basic maintenance of a healthy environment, the Kernel density curves of China's public health level and its sub-dimensions have shifted to the right to a certain extent, and there is no polarization phenomenon. Finally, the level of public health in China has a significant spatial correlation. Except for the northeast region, the growth rate of low-level public health provinces in China and the other three major regions is higher than that of high-level public health provinces, showing a certain convergence trend. In addition, the impact of economic development, financial pressure, and urbanization on the convergence of public health levels in the four major regions is significantly heterogeneous.

Synergy of pollution control and carbon reduction in China: Spatial–temporal characteristics, regional differences, and convergence

Promoting the synergy of pollution control (PC) and carbon reduction (CR) is an important strategy for ecological civilization construction in China. Based on constructing a measuring system for PC and CR respectively, we employ the coupling coordination model to determine the coupling coordination degree (CCD) between PC and CR in 30 Chinese provinces during 2006–2019, and analyze the spatial–temporal characteristics, regional differences, and convergence of the CCD between PC and CR from a dual perspective of east–west and south–north regional divisions. The results show that the average CCD between PC and CR increases from 0.8339 in 2006 to 0.8904 in 2019, suggesting that the two subsystems are in a well-coordinated stage. Moreover, China's CCD shows a “high in the east and low in the west, high in the south and low in the north” layout and exhibits a prominent spatial positive autocorrelation characteristic. Furthermore, the overall regional differences in the CCD of each province show an increasing trend initially, followed by a decreasing trend. The overall differences in east–west and south–north originate primarily from the cross-regional and within-regional difference, respectively. The results of the convergence model show that there is no σ convergence of China's CCD, while there exists β convergence in China and different regions. These findings provide empirical evidence and policy implications for facilitating the synergistic effect of PC and CR.

Does Industrial Agglomeration Promote Regional Innovation Convergence in China? Evidence From High-Tech Industries

The literature examining the importance of industrial agglomeration in innovation performance has expanded greatly in recent years, but the impact of industrial agglomeration, especially high-tech industrial agglomeration on regional innovation convergence, has been neglected. Using quantitative data from 30 provinces in China pertaining to the period 2005–2016, in this article, we analyze regional innovation convergence by focusing on three different types of convergence: σ-convergence, absolute σ-convergence, and conditional β-convergence. On the basis of the spatial effects, this article empirically investigates the impact of high-tech industrial agglomeration on regional innovation convergence in China by using spatial econometric models. The empirical results show that there is significant spatial autocorrelation in regional innovation. Thus, in the assessment of regional innovation convergence, the spatial effects should not be neglected. Moreover, our results demonstrate that regional innovation exists three different types of convergence (i.e., σ-convergence, absolute β-convergence, and conditional β-convergence). In addition, high-tech industrial agglomeration can promote regional innovation convergence. Finally, the grouping of high-tech industries into five subindustries shows that industrial agglomeration has different effects on regional innovation convergence. Overall, our findings provide convincing empirical evidence of the relationship between the high-tech industrial agglomeration and regional innovation convergence and valuable insights into how to realize regional innovation convergence.

On the Club Convergence in China’s Provincial Coal Consumptions: Evidence from a Nonlinear Time-Varying Factor Model

Coal has been the fundamental energy source supporting China’s energy supply and consumption. This paper examines convergence clubs for per capita coal consumption among 30 provinces of China between 1997 and 2019 by means of a nonlinear time-varying factor model. Meanwhile, the ordered probit model is further used to identify the causes affecting convergence. The results of analyses of data strongly support the existence of convergence clubs, indicating that there are four convergence clubs and one divergence group at the interprovincial level. Among the factors that potentially influence provincial coal consumption, the GDP-per capital, industrial structure, intensity of environment regulations and carbon emissions are positively related to per capita coal consumption, while investment in fixed assets, degree of openness to the outside world and technological progress are negatively related to per capita coal consumption. Increases in GDP-per capital, industrial structure, intensity of environment regulations and carbon emissions enhance the odds of belonging to a high coal consumption intensity club. Increases in investment in fixed assets, degree of openness to the outside world and technological progress reduce the odds of belonging to a high coal consumptions intensity club. These findings help policy makers to set coal production and consumption targets for different regions and reduce the differences in coal consumption across regions.

Dynamic evolution and driving forces of carbon emission efficiency in China: New evidence based on the RBM-ML model

The globe is being confronted with a tremendous challenge in the form of global warming, which is produced by emissions of carbon dioxide. To accomplish the double-sided objective of reducing carbon emissions while preserving a healthy rate of economic development, it is crucial to evaluate the driving forces of carbon emissions. In this study, the polar coordinate method is employed to improve the traditional Slacks-based Measure (SBM) method and propose a Ray SBM (RSBM). Additionally, the revised approach is paired with the Malmquist-Luenberger (ML) index to determine the carbon emission effectiveness (CFTP) of 30 prefectural regions in China between 2001 and 2019. The evolution features of the CFTP are examined by kernel density and spatial Markov chain. Moreover, according to the findings, CFTP in China has seen a moderate increase, with cutting-edge technological progress serving as the primary driver. The CFTP in eastern China is significantly lower than that in western China, and there is a discernible tendency toward the disparity becoming even wider. In addition, there is obvious club convergence in China's CFTP, which shows certain spatial agglomeration characteristics in the sample period. In accordance with the low-carbon economic theory and literature on CFTP, the variables of industrial structure, energy structure, technological progress, economic growth and environmental regulation are utilized to examine the driving factors for the spatial econometric model, and the corresponding spatial spillover effect is obvious.