Secondary Industry Research Articles

The impact of carbon emission trading schemes on China’s economic inequalities between and within urban and rural areas based on the satellite data: a county-level analysis

ABSTRACT Although China’s carbon emission trading schemes (CETS) garnered significant attention in the field of climate mitigation, limited data availability has hindered exploration into the impact of CETS on economic inequality at the county level in China. Given its potential to facilitate industrial upgrading and generate employment opportunities, the adoption of CETS holds promise for reducing economic inequality. To address data limitations, we employed a combination of gridded nighttime light data and land use data to estimate China’s county-level Dagum Gini coefficient and its components. Subsequently, we applied a difference-in-difference-in-difference method to examine how CETS affected economic inequalities between and within urban and rural areas in China. Our findings reveal that: (1) CETS significantly reduced overall economic inequality in counties with a high proportion of secondary industry output; (2) this reduction primarily occurred within urban and rural areas rather than between them. Further heterogeneity analysis demonstrates that while CETS effectively mitigated economic inequality between urban and rural areas in central and western regions, it did not achieve similar outcomes in the eastern region; (3) service industry development and rural GDP per capita served as important channels through which CETS reduced economic inequality within rural areas. Infrastructure development driven by CETS primarily addressed economic inequality within urban areas rather than rural areas.

The Spatial and Temporal Distribution, Flow Network and its Characteristics of Population in Henan Province

Based on the WorldPop center population data set and the dynamic monitoring data of China 's floating population, this paper analyzes the spatial and temporal changes of regional population and the characteristics of flow network and its influencing factors with the help of ArcGIS spatial analysis and mapping function and geographic detector model. It shows that: The regional difference of population spatial distribution in Henan Province is obvious and extremely uneven, and the population agglomeration speed of Zhengzhou metropolitan zone is obviously accelerated. The regional differentiation of population change in Henan Province is serious, and the population attraction of Zhengzhou is increasing, The population of Undertake industrial transfer zone such as Shangqiu and Zhoukou continued contraction. The population growth area and the population contraction area are more concentrated in space, showing the characteristics of spatial agglomeration. In addition, economic factors are still the main driving factors of population change in Henan Province. The influence of service industry on population change is increasing, and the explanatory power of traditional agriculture, forestry, animal husbandry and fishery and manufacturing industry on population change is decreasing. The integrated development of secondary and tertiary industries will further affect the future population distribution pattern of each region.

Coordination Relationship and Spatial Differentiation between Industrial Structure and Water Use Structure in Gansu Province

Taking Gansu Province as the research area, the coordination level and relationship between industrial structure and water use structure in Gansu Province were analyzed by the coordination degree and structure coefficient. On this basis, it is further divided into five regions, and the spatial differences of intra-regional and inter-regional coordination levels are explored by Gini coefficient. The results indicate that :(1) After the adjustment of industrial structure and water consumption structure, the proportion of secondary industry is reduced, and the water consumption is reduced. (2) The development of coordination degree is good, and the overall trend is low consumption, low efficiency and medium coordination water consumption mode. (3) The regional differences in industrial structure and water use structure in Gansu Province are prominent, especially in Hexi region and Gannan region, with a decreasing trend.

Konsep Industrialisasi, Transformasi Struktural

This research explores the concepts of industrialization and structural transformation, two phenomena that are interrelated and have a crucial role in the economic development of a country. Industrialization is the process by which a country or region shifts its economy from an agricultural to an industrial basis, involving increased production of goods and services through the introduction of new technologies and increased production capacity. Structural transformation, on the other hand, refers to fundamental changes in the structure of the economy, involving a shift from the primary sector (agriculture) to the secondary (industry) and tertiary (services) sectors. This study highlights how industrialization drives structural transformation by creating new jobs, increasing productivity, and changing consumption patterns and income distribution. This research also discusses factors that influence these two processes, including government policy, foreign investment, and technological innovation. Through analysis of various cases of countries that have successfully carried out industrialization and structural transformation, this research provides insight into effective strategies that can be implemented by developing countries to achieve sustainable and inclusive economic growth.

Impact of rural industrial integration on farmers' income: Evidence from agricultural counties in China

Rural industrial integration serves as an effective strategy to promote farmers' wealth, income, and overall rural revitalization. Drawing on the theories of national accounting and transaction costs, this study formulates a mechanism for how rural industrial integration increases farmers' income. It achieves this by increasing the value added of products, increasing short-term agricultural output, and reducing transaction costs. The research focuses on agricultural counties and districts in Liaoning and Shanxi provinces, and constructs a rural industrial integration index using the Herfindahl coefficient. The empirical analysis uses the PVAR model to test the relationship between the development of rural industrial integration and farmers' income. The results show that: the integration of primary and tertiary industries has a positive effect on the growth of farmers' income, while the integration of secondary and tertiary industries has only promoted the growth of farmers' income in Liaoning Province. Different integration models have different effects on the growth of farmers' income. Farmers' income significantly influences the development of rural industrial integration, but its effects vary across regions. Based on these findings, policy recommendations include tailoring strategies based on local resources and asset conditions, promoting vertical and horizontal integration of industrial chains, strengthening financial support, and encouraging the participation of new enterprises. The ultimate goal is to achieve comprehensive development of rural industries and increase farmers' incomes.

Study of Dholera Special Investment Region

This study examines the issues faced by Gujarat, India's Dholera Special Investment Region (DSIR) as it transitions to an entrepreneurial urbanization paradigm. The main focus of the study challenge is to comprehend the development trajectory of DSIR, specifically with respect to industrial expansion and sustainable urbanization, while tackling problems like land acquisition disputes and delays in infrastructure. The study uses a mixed-method approach, drawing on secondary literature analysis, industry reports, and direct data from governmental sources. It looks at the beginnings of DSIR, its growth plan, its corporate directional approach, and the wider socioeconomic effects of its evolution. The primary conclusions point to a paradigm shift toward a "entrepreneurial urbanization" model that is driven by funding from the private sector and government assistance. However, obstacles like property disputes and delays in infrastructure provide serious obstacles to the advancement of DSIR.

Spatial distribution, influencing factors and innovative development countermeasures of farmer cooperatives in Hunan Province, China

China’s rural reform is reliant on farmers' cooperatives as a key organization vehicle. It plays an important role in promoting rural revitalization. Such as, realizing the organic connection between small farmers and agricultural modernization. This study used the nearest neighbor index and kernel density estimation to analyze the spatial distribution and structural characteristics of farmer cooperatives in Hunan Province. It revealed the spatial differentiation law of cooperatives. Also using geographical detectors to figure out the main factors that affect the spatial distribution. The results show that: ① Hunan Farmers Cooperatives show significant spatial agglomeration. The overall spatial distribution shows the spatial characteristics of "one core, one circle, and multiple points". And the spatial distribution pattern of "large agglomeration, finger-shaped radiation distribution". Among them, the distribution of provincial demonstration cooperatives is relatively balanced. ② Cooperatives in six types of industries, such as planting, forestry, and feeding, showed agglomeration distribution. Different industrial cooperatives spread out in different ways, such as in an anti-"L" shape, a dual-core shape, or a one-center area. ③ The 24 influence factors selected from the five dimensions of the natural environment, social economic basis, production basis, output capacity, and facility basis have high, general, and weak influence on cooperatives' spatial distribution. The development and distribution of cooperatives mainly depend on resource endowment, social and economic development level, and market dependence. The spatial distribution heterogeneity of different professional cooperatives is mainly affected by slope, per capita disposable income of rural residents, road density, and other factors. ④ The progression of farmer cooperatives in Hunan Province should prioritize high-quality development, emphasizing the need for innovative approaches and transformative strategies within rural industrial organizations. It is imperative to optimize the spatial distribution of cooperatives, strategically contributing to the establishment of a novel framework for modern agricultural development in Hunan Province. Additionally, there is a critical emphasis on spearheading collaborative initiatives among cooperatives of varied industrial types, aimed at fostering the integrated development of rural primary, secondary, and tertiary industries.

Spatial response of urban land use intensity to ecological networks: a case study of Xi'an Metropolitan Region, China.

In the face of the persistent degradation of ecological environments and fragmentation of ecological networks brought about by rapid urbanization, this study focuses on examining the interaction between urban land use intensity and ecological networks in the Xi'an Metropolitan Region (XAMR), China, and their impact on ecological equilibrium and sustainable development. By comprehensively evaluating the changes in land use intensity in XAMR from 2010 to 2020, the aim is to underscore the pivotal role of ecological networks in maintaining urban ecological balance and promoting sustainable development. The findings indicate a transition in land use intensity in the XAMR from low to high concentration, reflecting an intensification in land resource utilization during urbanization. However, the establishment and management of ecological networks can significantly enhance urban ecological security and biodiversity. Notably, this research identified crucial ecological corridors and source areas, augmenting the connectivity of urban green infrastructure and providing vital support for urban biodiversity. Additionally, a significant finding of this study is the spatial spillover effects generated by socioeconomic factors such as the proportion of tertiary and secondary industries and per capita GDP through the ecological network, which have profound impacts on land use intensity in the surrounding areas. These insights offer a novel understanding of the complex interactions within urban ecosystems, emphasizing the importance of incorporating ecological network construction in urban planning. Overall, through a comprehensive analysis of the relationship between the ecological network and land use intensity in the XAMR, this study proposes new directions for urban ecosystem management and land use planning, highlighting the significance of scientific ecological network planning and management in achieving long-term sustainable development in urbanization processes.

Low blood glucose and fatigue accumulation at peak hours of occupational trauma in secondary industry workers

Objectives. The incidence of occupational traumatic injuries caused by human error has been reported to occur at 11:00 and 8–9 h after commencing work. Impaired attention is closely related to the incidence of these accidents. Therefore, this study aimed to clarify the changes in blood glucose, fatigue and stress response hormone levels over time among workers in a secondary industry. Methods. The blood glucose and subjective fatigue levels of 26 male secondary-industry workers were measured on workdays. In addition, the cortisol and dehydroepiandrosterone levels in saliva were measured on one workday and one holiday. Results. Blood glucose levels at 11:00 and 17:30 on the workday were significantly lower than those at 09:30. Moreover, hypoglycemia was observed in some participants. A significant increase in subjective fatigue levels was observed during the workday. However, no significant differences in salivary cortisol levels were observed between the workday and the holiday at any time point. Conclusions. Blood glucose levels decreased and subjective fatigue levels increased at the time points that occupational accidents were reported to occur most frequently during work. These factors may contribute to human errors due to impaired attentional function.

Researching the Influence of Rural University Campuses on Rural Economic Development: Evidence from Chinese Counties between 2001 and 2020

While there have been studies on the relationship between higher education institutions and regional economic growth, few have delved into the economic impact of decentralized higher education institutions at the county level and associated reginal disparities in terms of socio-economic development. Utilizing the data of the Chinese universities that started to establish their campuses in counties since the year 1999, this study investigates the influence of rural university campuses on county-level GDP and industrial composition spanning from 2001 to 2020. It also delves into the temporal dynamics and regional discrepancies associated with this impact. The findings of this study show that (a) rural university campuses wield a notable positive influence on the GDP of their respective counties, particularly shaping the structure and ratio of secondary and tertiary industries; (b) the magnitude of this effect is contingent upon the duration of campus establishment and growth, intensifying over time; (c) variations in this impact are evident across the eastern, central, and western regions of China, where there are vast socio-economic differences. This study underscores the significant spillover effect of higher education decentralization on county-level economies and advocates for the pivotal role of rural university campuses in propelling county-level economic progress. Additionally, it proposes coordinated policy support from national, regional, and rural university campus authorities; the establishment of requisite support structures; and the comprehensive consideration of regional nuances.

Assessment of the effects of extreme temperature on economic activity

The effects of climate change on the economy are becoming increasingly evident. Based on information of all newly registered enterprises in China from 2000 to 2019, we discuss the relationship between heatwave and entrepreneurial activities at county level. Results indicate that extremely high temperatures can negatively affect entrepreneurial activities. Moreover, after considering endogeneity issues and conducting a series of robustness checks, the conclusion remains. In addition, mechanism testing shows that extremely high temperatures reduce the attractiveness of entrepreneurship by generating fiscal pressure effects, industrial dependence effects, and leading demonstration effects. Finally, heterogeneity analysis indicates that the adverse effects of extremely high temperatures will be alleviated in areas with large populations and high levels of education and healthcare. Different from the relief effect brought by the vigorous development of the secondary and tertiary industries, regions that rely more on the primary industry suffer more severe damage.

Effects of internal migrants' health on economic resilience in China's Yangtze River Delta urban agglomeration: moderating effects of basic public health services.

Internal migrants constitute a significant generality in the socioeconomic development of developing countries. With the frequent occurrence of major public health emergencies, obstacles to labor supply due to health issues among internal migrants not only affect their livelihood stability but also urban economic resilience. Moreover, the design of basic public health service systems tends to favor local residents over internal migrants, further exacerbating the health and employment risks of internal migrants. As a result, urban economic resilience faces significant challenges. The objective of this study was to deconstruct economic resilience into economic resistance and recovery abilities, investigate the net effect and its heterogeneity of internal migrants' health on economic resilience in China's Yangtze River Delta urban agglomeration (CYRD), and the mediating effect from labor participation rate and labor time supply, as well as the moderating effect of basic public health services. Based on the China Migrants Dynamic Survey data (CMDS), the study empirically estimated the effects of internal migrants' health on economic resilience in CYRD through microeconometric analysis methods, mediating and moderating effect model. Our findings indicate that internal migrants' health has a positive effect on economic resilience in CYRD. For each unit increase in migrants' health, it will drive up the average economic resistance ability by 0.0186 and the average recovery ability by 0.0039. Secondly, the net effects of migrants' health on economic resilience show significant structural differences, industry and city heterogeneity. The effect of migrants' health on economic resistance ability is significantly higher than that on economic recovery ability; The effect of migrants' health on economic resilience of the secondary industry is higher than that of the tertiary industry; The cities with high economic resistance and recovery abilities have more prominent positive effect from migrants' health. Thirdly, migrants' health not only has a direct effect on the economic resistance and recovery abilities, but also has a mediating effect on which through labor participation rate and labor time supply. Enhancing the accessibility and quality of basic public health services is beneficial for enhancing the positive effects of internal migrants' health on economic resilience.

How effective is the reduction of major pollutants in thermal power plants under the ultra-low emission policy?

In 2015, the Chinese government set ultra-low emission standards for thermal power to alleviate the pressure of increasing total pollutants from energy demand. This paper analyzes the policy effect of ultra-low emission in different regions based on panel data of 1202 thermal power enterprises, and the results of hierarchical linear model show that the total amount of air pollutants emitted by thermal power enterprises showed a decreasing trend during 2017–2021, realizing the dual control of concentration and total amount. Due to the differences in primary energy structure, industrial structure and economic development level of different regions, the total emission reduction of thermal power pollutants is affected differently. First, the proportion of the region's secondary industry in the region's GDP is negatively correlated with the decrease of the total pollutant emission of local thermal power enterprises. Second, the higher the per capita GDP of the region, the more significant the decrease in the total amount of pollutants, economic development is conducive to pollutant emission reduction. Third, the higher the proportion of thermal power in local energy, the more obvious the reduction of total pollutant emissions of thermal power enterprises, indicating that the implementation of ultra-low emission policies in these regions is more thorough. In addition, the environmental protection tax plays a positive role in the total emission reduction, and the higher the sulfur dioxide tax rate, the more significant the reduction of total pollutants of thermal power enterprises. To further reduce the total amount of pollutants in thermal power, more coordinated efforts of environmental and economic policies are needed.

Analysis of the Coupling Coordination between the Ecosystem Service Value and Urbanization in the Circum-Bohai-Sea Region and Its Obstacle Factors

In light of the tremendous pressure for improving urbanization levels and expanding construction land on ecosystems, regional sustainable development is premised on the coordinated development of the ecological environment and urbanization. This paper focuses on the Circum-Bohai-Sea Region and assesses the ecosystem service value (ESV) and urbanization level using the equivalence factor and entropy-weighted TOPSIS methods. Based on these assessments, it examines the coupling coordination between the ESV and urbanization as well as the obstacles to this coordination, utilizing the coupling coordination degree model, spatial autocorrelation model, and obstacle model. The results revealed several key findings. First, the Circum-Bohai-Sea Region experienced a continuous improvement in the urbanization level from 2005 to 2020, which presented a “center–periphery” spatial pattern. Overall, the ESV exhibited an N-shaped trend, namely, initially increasing, then decreasing, and then rapidly increasing. The ESV per unit of area exhibited a spatial difference, with the boundary of Baoding and Cangzhou as the dividing line. The ESV per unit of area in the northern parts was higher than that in the southern parts. Second, the degree of the coupling coordination between the ESV and urbanization exhibited an inverted U-shaped trend, initially increasing and then slightly decreasing. It also exhibited significant spatial heterogeneity, with the degree of the coupling coordination in the northern parts being higher than that in the southern parts and that in the central parts being higher than those in the eastern and western parts. Additionally, the ESV showed a significant spatially positive correlation with urbanization. H-H clusters were predominantly found in central and southern Liaoning Province, while L-L clusters were primarily located in southern Hebei Province and western Shandong Province. Third, the obstacle factors remained stable during the study period. The top five obstacles in the ESV system were the water resource supply, nutrient cycling maintenance, raw material production, aesthetic landscape, and food production. Moreover, the top five obstacles in the urbanization system were the number of college students per 10,000 people, population density, number of health technical personnel per 10,000 people, per capita road area, and proportion of secondary and tertiary industry output values.

Impacts of spatial and temporal patterns and economic development on carbon emissions in Chinese cities

With the economic and social development and the improvement of peoples living standards, the urban carbon emission increases. Studying the influence of industrial structure and spatial patterns on carbon emission under the economic development of different cities can help to find the main factors affecting carbon emission, formulate policies to solve the problem according to local conditions, and provide an important scientific basis for the transformation of economic growth mode and the construction of low-carbon cities. This paper draws conclusions by analyzing the trend curves of urban carbon emissions and economic factors over the years. Different regions of the citys economic development potential differences are obvious, and the potential for greater spatial concentration of cities; citys economic development potential in the spatial and temporal distribution of key cities and major urban agglomerations as the basis for the point - line - surface in order to promote. economically developed cities, the total carbon emissions, carbon emissions growth rate of a declining trend; economically underdeveloped areas, the total carbon emissions, carbon emissions growth rate of a year-on-year trend; the degree of carbon emissions and the degree of prosperity of the secondary industry is closely linked. Chinas urban carbon emissions have a significant positive spatial correlation between 2006 and 2016, the cold spot area of urban carbon emissions is relatively stable, mainly distributed in the eastern and southern economic zones, while the hot spot area is mainly distributed in the northwest, northeast and the middle reaches of the Yellow River economic zone.

The Impact of Foreign Direct Investment, Green Technology Innovation and GDP on CO2 Emissions in Western China: A Static Panel Data Analysis

This study investigates the impact of FDI, green technology innovation and GDP on CO2 emissions in the western region of China. This study applies the extended STIRPAT model, selects the relevant data of nine provinces in western China from 2000 to 2019, applies the static panel data analysis method, compares and analyses the estimation methods of Pooled OLS, fixed effect and random effect, and finally adopts the robust standard error estimation method of fixed effect. The results of the robust standard error estimation indicate that, in addition to the negative impact of green technology innovation on CO2 emissions, CO2 emissions are positively impacted by FDI, GDP, population, and the proportion of the secondary and tertiary industries. Therefore, reasonable introduction of FDI and improving green technology innovation levels are crucial in reducing CO2 emissions in the western region of China.

Land-Use Transitions and Its Driving Mechanism Analysis in Putian City, China, during 2000–2020

Investigating the spatial-temporal evolution of land use and its driving forces provides a scientific basis for policy formulation, land-use structure adjustment, and ecological civilization development. Using the Google Earth Engine (GEE) platform, this study analyzed remote sensing images from 2000, 2010, and 2020 to derive basic land-use data for Putian City and its five districts and counties. These data were then systematically analyzed using methodologies such as Single Land-use Dynamics and Geo-informatic Tupu to reveal the characteristics of land-use transitions (LUTs), and the spatial-temporal evolution pattern over the past two decades in Putian City, China. Subsequently, socioeconomic conditions and macro policies were identified as driving factors to further explore the mechanisms behind land-use evolution in the study area through canonical correspondence analysis (CCA). The findings revealed that: (1) The predominant land-use structure in Putian City consisted mainly of cultivated land and forest land, with other land types interspersed within them, while built-up land exhibited continual outward expansion. (2) Various regions within Putian City exhibited varying degrees of abandoned farmland, ultimately transforming into wasteland (grassland) with weed growth, presenting significant challenges for ensuring food security and mitigating the conversion of cultivated land to non-agricultural and non-grain uses. (3) Specific macro-economic development objectives during distinct periods, particularly urban expansion and the growth of the secondary industry resulting from municipal and county mergers, emerged as pivotal factors driving the spatial and temporal evolution of land use and influenced the differential distribution pattern across Putian City. Consequently, this study suggests bolstering scientific planning and implementing effective regulations concerning land use, and it advocates for the efficient utilization of space-time resources pertaining to cultivated land, integrating them with agriculture, culture, and tourism endeavors. Such measures are proposed to ensure the harmonized and sustainable development of the regional ecological economy.

Migration networks, export shocks, and human capital acquisition: Evidence from China

We examine the impact of export shocks proxied by destination countries’ tariffs on the post middle school enrollment of the rural population in China. We complement the literature by examining the across-region spillover effects of export shocks through initial migration networks. We find that the reduction of export tariffs at both the local and migration-destination prefectures significantly decreases post middle school enrollment of the 16–18 years old cohort, but the latter is stronger. Further analysis suggests that employment in the secondary industry rises significantly with the reduction of export tariffs, which improves job opportunities and thus increases the post middle school dropout rate.

Investigating the effect of industry-specific economic distance on the prediction of intercity population movement

Intercity population movement has been extensively studied since it is closely related to human society. Currently, city industry structures play dominant roles in the direction of population movement. Yet, the extent to which different kinds of industry proximity influence human mobility remains unclear. In this study, we introduce the concept of intercity industry proximity, regarded as economic distances, to forecast intercity population movement using a relational graph convolutional network. Our findings demonstrate the effectiveness of this framework in learning information from 18 industry proximity networks. Using this framework, we investigate the impact of distinct industries on population movement by traversing each industry as input separately. Results show that while all industries exhibit favorable predictive performance, slight differences exist. Specifically, the primary industry emerges as the most influential predictor of population movement, followed by secondary industries, whereas certain tertiary industries exert comparatively minimal effects. We also examine the influence of proximity thresholds for graph-generating on model performance. Theoretical explanations concerning face-to-face interactions for the diffusion of tacit knowledge are discussed, and policy implications are provided to enrich the current understanding of population movement.

Research on Short Term Prediction of Electricity Demand in Hubei Province

The balance of electricity supply and demand is the basic condition for promoting the economic development of our country and improving the living standards of the people, and scientific forecasting of electricity demand is the premise of ensuring the balance of electricity supply and demand. Hubei Province is superior in geographical location, and its electricity demand and economic aggregate both rank high in the country, but due to the direct impact of the epidemic, its electricity demand has been affected. This paper uses OLS regression to obtain the linear regression equation of the three indicators of GDP and the proportion of the secondary industry structure before the epidemic from 2005 to 2018, and uses the Gray Forecast Model-assisted scenario analysis method to analyze the electricity consumption of Hubei Province under the influence of multiple factors, and predicts the electricity consumption of Hubei Province from 2019 to 2021 after removing the impact of the epidemic, and makes a short-term forecast of the electricity demand of the province from 2024 to 2029.