Disposable Income Of Urban Residents Research Articles

Analysis of affordability differences for rare diseases in China: a comparison across disease types and regions

BackgroundChina has implemented policies to make rare diseases more affordable. While previous studies evaluated overall affordability, few have examined affordability differences across regions and disease types. Given the vastness of China and varying medical policies across cities, this study assesses the affordability of rare diseases based on China’s First List of Rare Diseases (CFLRD), National Reimbursement Drug List (NRDL), and outpatient chronic and special disease policies in each prefecture.MethodSix rare diseases were selected and the average annual treatment cost of all relevant drugs in NRDL was calculated for each disease. Based on the WHO/HAI standardized approach, the study analyzed 289 cities with outpatient chronic and special disease policies, measured the security levels by the actual reimbursement ratio of Basic Medical Insurance (BMI) and affordability by the ratio of individual expenses after reimbursement to the annual disposable income of urban residents in the province. The security levels and affordability differences across disease types and provinces were analyzed using the Mann-Whitney U test and the K-W test.ResultThe affordability of rare diseases varied significantly on the disease types and annual treatment cost. Diseases with an annual treatment cost below 100 000 yuan are affordable to all prefectures even with low reimbursement rates, while those with a higher treatment cost were not affordable in at least 80% of prefectures even though the reimbursement ratio is high. The affordability of the same disease varies significantly across provinces and municipalities. Outpatient chronic and special diseases insurance and critical illness insurance, and the inconsistencies between them, result in regional differences.ConclusionAlthough China has made progress in improving the affordability of rare diseases, significant differences persist between cities and diseases. The study suggests the optimization of the BMI system and explores independent funds and innovative insurance models to enhance the affordability of rare diseases, particularly those with extremely high treatment costs.

"Machine replacement" or "job creation": How does artificial intelligence impact employment patterns in China's manufacturing industry?

Artificial intelligence (AI), as an important engine for promoting high-quality economic development, should not be overlooked in terms of its impact on the employment of the labor force while promoting the digital and intelligent transformation of industries. In the face of the complex international environment and non-systemic shocks, it is of great significance to explore whether it is "machine replacement" or "job creation" in the process of the integration of AI and industry, as well as the impact of technological progress on the employment pattern of the labor force, in order to promote the economic development, respond to and solve the employment problem. It is of great significance to promote economic development and cope with and solve the employment problem. Based on the task model, this paper analyses the mechanism of the impact of AI on the employment pattern of manufacturing industry. Meanwhile, based on the provincial panel data of China's manufacturing industry from 2011 to 2020, it empirically examines the impact of AI on the total employment, employment structure and employment quality of the labor force, and analyses the multiple responses of AI on the employment pattern of the manufacturing industry. The study shows that: Firstly, the level of development of AI and the total amount of employment is a positive U-shaped relationship, the short term is dominated by the substitution effect, and the long term is dominated by the creation effect; Secondly, with regard to the employment structure, low-skilled labor is more likely to be replaced. The financial, accommodation and catering industries are relatively less affected by the spillover effects of the manufacturing industry; Third, with regard to the employment quality, the gap between urban and rural incomes has eased, with per capita net income of rural residents rising to a higher degree than per capita disposable income of urban residents. Thus, in order to further address the impact of AI on the employment patterns of the labor force, the level of AI development should be increased while expanding employment channels, paying attention to labor force skills training, reinforcing the leading role of developed regions, and accelerating regional integration and urban-rural integration, so as to share the dividends of technological progress.

Policy implications for synergistic management of PM2.5 and O3 pollution from a pattern-process-sustainability perspective in China

In recent years, the pattern of air pollution in China has changed profoundly, and PM2.5 and surface ozone (O3) have become the main air pollutants affecting the air quality of cities and regions in China. The synergistic control of the two has become the key to the sustainable improvement of air quality in China. In this study, we investigated and analyzed the spatial and temporal distribution patterns, exposure health risks, key drivers, and sustainable characteristics of PM2.5 and O3 concentrations in China from 2013 to 2022 at the national and city cluster scales by combining methodological models such as spatial statistics, trend analysis, exposure-response function, Hurst index, and multi-scale geographically weighted regression (MGWR) model. Ultimately, a synergistic management system for PM2.5 and O3 pollution was proposed. The results showed that: (1) The PM2.5 concentration decreased at a rate of 1.45 μg/m3 per year (p < 0.05), while the O3 concentration increased at a rate of 2.54 μg/m3 per year (p < 0.05). The trends of the two concentrations showed significant differences in spatial distribution. (2) Population exposure risks to pollutants showed an increasing trend, with PM2.5 and O3 increasing by 55.1 % and 42.7 %, respectively. The annual deaths associated with exposure to PM2.5 and O3 demonstrated a decreasing and inverted U-shaped trend, respectively, with annual average deaths of 1.312 million and 98,000. Significant regional disparities in health risks from these pollutants were influenced by socio-economic factors such as industrial activities and population density. In the future, it is expected that more than half of China's regions will be exposed to rising risks of PM2.5 and O3 population exposure. (3) Key drivers of regional exacerbation in PM2.5 and O3 levels include the number of industrial enterprises above designated size (NSIE) and population agglomeration (PA), while the disposable income of urban residents (URDI), technological innovation (TI), and government attention level (GAL) emerged as primary factors in controlling pollution hotspots, ranked in order of influence from greatest to least as TI > GAL > URDI. Overall, this study sheds light on the current status of air pollution and health risk sustainability in China and enhances the understanding of future air pollution dynamics in China. The results of the study may help to develop effective targeted control measures to synergize the management of PM2.5 and O3 in different regions.

Evaluation of the Quality of the Age-Friendly Environment in Liaoning Province

The age friendliness of an environment is significant for improving the quality of life of the elderly. This metric is an important measure used by the international community to address the challenges of population aging. In order to explore effective ways to improve the quality of an age-friendly environment, this study considers the theoretical framework of the World Health Organization and combines China’s demographic and policy conditions to develop an urban-scale indicator system for the evaluation of the age-friendly environment (AFE) by including the dimensions of social and physical environments and municipal services. The entropy method and multiple linear regression were used to study the changes and influencing factors of the quality of AFE in 14 prefecture-level cities in Liaoning Province. The research results are as follows. First, temporally, the comprehensive quality of AFE in the cities in Liaoning Province was at a relatively low level, and the overall trend was decreasing. During the evaluation period, the level of age friendliness in various cities was generally low, with a relatively small number of cities scoring higher. Second, spatially, significant regional differences in the age friendliness of the environment existed, which showed spatial patterns of “high in the middle and low on both sides” and “strong in the south and weak in the north”. Third, the dimensions were in the order of physical environment &gt; municipal services &gt; social environment. The social environment was weak for the construction of AFEs in Liaoning Province, and efforts are required to strengthen it in the future. Fourth, aging rate was negatively correlated with the level of AFE. The positively correlated factors were in the order of expenditure for urban and rural community affairs &gt; per capita GDP &gt; per capita disposable income of urban residents. This study provides insights for cities to improve the quality of AFEs, actively respond to population aging, and help promote WHO initiatives in developing countries.

Research on the Factors Influencing Tourism Revenue of Shandong Province in China Based on Uncertain Regression Analysis

According to the analysis of historical tourism data, it was found that tourism revenue is influenced by multiple factors, and there exists a linear relationship between these factors and tourism revenue. Therefore, this paper employs a linear regression model to investigate the factors influencing tourism revenue. However, research on tourism data has found that the disturbance term of the linear regression model is not frequency-stable. This indicates that the disturbance term should be an uncertain variable rather than a random variable. Therefore, this paper adopts an uncertain linear regression analysis model and employs the tourism data of Shandong Province in China from 2011 to 2020 as the sample to investigate the factors influencing tourism revenue. The study provides parameter estimation and residual analysis of the model, as well as predictions and confidence intervals of tourism revenue. Additionally, through an uncertain hypothesis test, it was verified that the adopted model fitted the relevant tourism data well. The results show that factors such as the number of travel agencies, railway length, domestic tourist numbers, and per capita disposable income of urban residents have a significant impact on tourism revenue. Based on the study, recommendations and measures for improving tourism revenue of Shandong Province are proposed.

Impact of regional accessibility on urban residents' income in China: A bidirectional-fixed panel model.

The income gap between regions and its expansion are the main manifestations of the imbalanced and inadequate economic development in China. High-speed railway (HSR) construction is regarded as an important method to drive domestic demand, drive the pulse of the economy, and promote the coordinated development of regions. Based on the opening of HSR and the acceleration of ordinary railways, we used the weighted average travel time model and accessibility coefficient to estimate the changes on accessibility in 286 cities at prefecture-level and above from 2000 to 2018. Then, the influence mechanisms of improving regional accessibility on urban residents' income were estimated by using the bidirectional-fixed effects panel model and the recursive model respectively. We found that: (1) The accessibility of urban areas has been greatly improved due to the opening of HSR and the acceleration of ordinary railway, among which the improvement of HSR cities is greater. (2) The improvement of regional accessibility significantly promoted the income growth of urban residents, and the increase of the regional accessibility coefficient by 1 unit led to an average increase of 2140 yuan in the per capita disposable income of urban residents. (3) There is regional heterogeneity in the impact of improving regional accessibility on urban residents' income, and it has a significant effect on the eastern and northeastern regions. It has a greater positive effect on improving the income of residents in central cities compared with peripheral cities. (4) Regional accessibility can promote urban income growth through regional employment and fixed asset investment. In the future, the transportation network should be further improved to facilitate the regional economic cycle, strengthen the coordination and complementarity of regional economies, and promote regional economic integration so as to promote the improvement of resident income level and the common prosperity of the people.

Analysis of the Grey Correlation Between Higher Education and Economic Development

Regional higher education and economic development are inseparable, so it is of great significance to study the correlation degree between higher education and economic development. This paper integrates the relevant evaluation indexes, and uses the grey correlation analysis method to explore the degree of mutual influence between higher education and economic development in Guangxi. The results show that the gross product of primary industry, per capita disposable income of urban residents and urbanization rate are the key factors affecting the level of higher education; the Di-Clark theorem is not applicable to the industrialization development of Guangxi; the increase of institutions and full-time teachers and the investment of education funds are the main driving force for higher education to promote economic development. Finally, to provide policy suggestions for the high-quality development of higher education and economy in Guangxi.

Does subway mileage affect urban housing prices? An economic growth perspective

ABSTRACT Studying the mechanism by which urban subway construction in China increases housing prices can help deepen the understanding of the factors that rises in housing prices and may assist the government to conduct reasonable macro-control of the real estate market. This article takes unbalanced panel data from 31 major cities in China as research samples and studies the mechanism by which urban subway construction increases housing prices by influencing urban economic growth. Our findings are as follows: (1) Subway construction promotes urban economic growth, and urban economic growth, from both the demand and supply sides, increases housing prices by increasing the disposable income of urban residents and the purchase price of residential land. (2) Urban subway construction increases city land purchase prices by affecting investors’ expectations of urban land development through the regulating effects of urban economic growth, which in turn increases housing prices. (3) Effective policy measures aimed at managing the speculative impact of metro construction on housing prices need to be viewed for the expectation management of housing and land speculative demand from both the demand side and the supply side.

Influencing factors analysis of corn price fluctuation in shaanxi province, CHINA

Corn is one of the most important grain crops in China, and also in Shaanxi Province. In order to master the changing law of corn market, realize reasonable regulation and control, and promote the stable development of the market, it is necessary to conduct in-depth research on the influencing factors of corn price fluctuation in Shaanxi Province. Based on the data of Shaanxi Province from 2000 to 2021, in the present study, the main factors affecting the price fluctuation in Shaanxi Province was explored by using factor analysis method. Eight indexes including corn yield, production cost, disaster-affected area, disposable income of rural residents, disposable income of urban residents, corn demand, wheat price index and consumer price were selected as factors affecting corn price fluctuation. Results showed that the disaster area and corn demand were the main factors affecting the corn price fluctuation in Shaanxi Province, and the disposable income of urban and rural residents had little impact on the corn price fluctuation. Governments and industry groups can therefore take preventive measures to limit the impact of major climate events on corn markets and economies. It also assesses the appropriate proportion of corn used for feed and energy production to ensure adequate supply and stable prices. Bangladesh J. Bot. 52(2): 607-612, 2023 (June) Special

Influencing factors analysis of corn price fluctuation in shaanxi province, CHINA

Corn is one of the most important grain crops in China, and also in Shaanxi Province. In order to master the changing law of corn market, realize reasonable regulation and control, and promote the stable development of the market, it is necessary to conduct in-depth research on the influencing factors of corn price fluctuation in Shaanxi Province. Based on the data of Shaanxi Province from 2000 to 2021, in the present study, the main factors affecting the price fluctuation in Shaanxi Province was explored by using factor analysis method. Eight indexes including corn yield, production cost, disaster-affected area, disposable income of rural residents, disposable income of urban residents, corn demand, wheat price index and consumer price were selected as factors affecting corn price fluctuation. Results showed that the disaster area and corn demand were the main factors affecting the corn price fluctuation in Shaanxi Province, and the disposable income of urban and rural residents had little impact on the corn price fluctuation. Governments and industry groups can therefore take preventive measures to limit the impact of major climate events on corn markets and economies. It also assesses the appropriate proportion of corn used for feed and energy production to ensure adequate supply and stable prices. Bangladesh J. Bot. 52(2): 607-612, 2023 (June) Special

A two-stage credit scoring model based on random forest: Evidence from Chinese small firms

Small firms are major contributors to most economies, often supported by government policies. However, the credit scoring of small firms is complicated and costly, making it a challenging field of research. Using loan data from 3045 small firms in China, we design a two-stage expert system for default prediction that quantifies the variables and thresholds that have a key impact. Firstly, we use SMOTE to deal with the imbalanced data and secondly, we employ random forest to build predictive credit features. Dominance analysis shows that, when making default assessments on Chinese small firms, it is important to consider not only financial factors, but also non-financial and macroeconomic factors. In particular, the net cash profit, the firm's legal disputes and the per capita disposable income of urban residents are key factors in credit scoring. Robustness tests show that our proposed methodology performs better than other machine learning models, and this result is robust with observations from other countries.

Influences of Climatic Factors and Human Activities on Forest–Shrub–Grass Suitability in the Yellow River Basin, China

Natural and human factors co-drive changes in vegetation type and distribution. In this study, we constructed an index system covering 17 natural and human activity indicators in six dimensions by using climate data, county-level human activity data, and forest–shrub–grass suitability data from 448 sample counties in the Yellow River Basin of China in 2018. On this basis, we evaluated the influence of human activities and climatic factors on vegetation suitability using multiple regression and relative importance analysis methods. The multiple regression results demonstrate that climatic factors had positive effects on vegetation suitability in the Yellow River Basin, while the influence of human activities on vegetation suitability varied according to the situation. Specifically, economic factors such as per capita disposable income of urban residents and per capita disposable income of rural residents; urbanization factors such as population density, urbanization rate, and construction land area proportion; social development factors such as road density; and agricultural production factors such as the cultivated acreage proportion and the value added of the primary industries proportion all influence vegetation suitability. There is a great regional heterogeneity in the effects of human activities such as economic factors and urbanization factors on vegetation suitability. The relative importance analysis results show that the relative importance of the factors influencing vegetation suitability in the Yellow River Basin was as follows, in order of importance: climatic factors &gt; agricultural production factors &gt; urbanization factors &gt; ecological projects &gt; social development factors &gt; economy factors; however, except for climatic factors, the importance of other influencing factors varied from region to region. This study provides a theoretical basis for optimizing vegetation adjustment schemes and forest and grass ecosystem layout according to regional characteristics.

Coordinated Development and Sustainability of the Agriculture, Climate and Society System in China: Based on the PLE Analysis Framework

Nowadays, frequent climate extremes exert a serious impact on agricultural production and social development, which is seldom studied in the previous literature. Production–Living–Ecological (PLE) is a useful analysis framework, and China is a suitable model for such study. This paper takes the Huai River Eco-Economic Belt (HREB), an important agricultural zone in China, to study the relationship among agricultural production (P), society (L), and climate change (E), which is referred to as APLE. This paper constructs a coupled coordination evaluation index system for the APLE system and uses coupling coordination degree models and geographic detector to study the spatial and temporal evolution of the coordinated development of 34 counties (cities) in the HREB from 2009 to 2018. The results show the following: (1) The development of the agricultural subsystem and the social subsystem formed a “scissors difference” from 2009 to 2014, and the three subsystems showed a slight upward trend during 2014–2018. (2) The coupling and coordinated development of the APLE system in the HREB was generally stable, and the coupling coordination degree was improved from low-grade and slightly uncoordinated to barely and primarily coordinated. Furthermore, the spatial differentiation of the coupling coordination degree shows a clear pattern of being high in the southeast and low in the northwest. (3) The main influencing factors are the drought and flood protection rate, the effective irrigation rate, the per capita electricity consumption in agriculture, the number of beds in healthcare facilities per 10,000 people, the per capita disposable income of urban residents, the annual average temperature, and the annual precipitation. (4) The spatial–temporal evolution of the coupling and coordinated development of the APLE system is the result of the comprehensive effect of internal driving forces such as food security, the consumption level of rural residents, and the development level of urbanization construction, and external driving forces such as government public welfare and natural conditions.

Discussion on the Influencing Factors of Housing Prices in Shandong Province

Aiming at the influencing factors of commercial housing prices in Anhui, based on the relevant data of the 2000~2020 Shandong Statistical Yearbook, three explanatory variables of actual GDP, actual per capita disposable income of urban residents and total population were selected, and a multiple linear regression model was established by Eviews software, and econometric test methods such as multicollinearity, heteroscedasticity and autocorrelation were tested and the model was modified. The results show that the per capita disposable income and total number of urban residents have a positive impact on the price of commercial housing in Shandong Province. Based on the research conclusions, it is proposed to provide a reference for the stable development of the commercial real estate industry in Shandong Province.

Comprehensive quantitative evaluation of the water resource carrying capacity in Wuhan City based on the “human–water–city” framework: Past, present and future

Given China's rapid urbanization process, the study of water resource carrying capacity (WRCC) has important theoretical and practical significance for urban sustainable development. In this paper, a “human–water–city” (HWC) framework was proposed that offers a comprehensive consideration of the development of human society, water quality and quantity, and the progress of urban construction. Based on this framework, we established an HWC evaluation indicator system and constructed the WRCC-HWC approach, to assess, compare, and forecast the WRCC. Taking Wuhan, China, as an example, principal component analysis (PCA) was adopted to evaluate the current (2009–2019) and future (2020–2030) WRCC-HWC. Specifically, global climate models (GCMs) and a grey model, GM (1,1), were used to forecast the value of the future index system. The results show that the WRCC-HWC in Wuhan gradually increased from −3.04 to 3.23 during 2009–2019, being mainly affected by the income of urban residents, per capita GDP, reuse ratio of water used by industry, built-up area, and the output value of new and high-tech industry. With a rapid growth rate from 2011 to 2016, the WRCC-HWC reached the Grade I (excellent) state in 2016. In addition, the forecast results show that, with the exceptions of precipitation and good air quality rate, all HWC indicators show upward trends from 2020 to 2030 in Wuhan. In particular, the per capita disposable income of urban residents (N1), per capita GDP (N2), and the output value of new and high-tech industry (N11) have faster growth rates, with relative growth rates from 2020 to 2030 exceeding 100%. Correspondingly, the WRCC-HWC from 2020 to 2030 were predicted to grow steadily each year, with a higher absolute growth rate starting in 2025. This study supports a comprehensive understanding of the current and future situation for WRCC-HWC in Wuhan and can provide a reference for the formulation of scientific and sustainable development strategies.

Dynamic Resource Allocation and Forecast of Snow Tourism Demand Based on Multiobjective Optimization Algorithm.

This paper aims to map the task of reliable transmission of wireless sensor networks. At the same time, this paper transforms the mapping problem of wireless sensor networks into a problem of reducing the energy consumption of mapping under many constraints such as reliability and scheduling length and uses discrete particle swarm optimization algorithm to map. For optimization, the algorithm performs iterative calculations to obtain the best mapping node for each operation so that the inertia coefficient of the existing particle swarm optimization algorithm is improved and linearly minimized with the number of iterations. When resource-demanding tasks need to allocate dynamic resources to multiple nodes to complete collaboratively, adding the mapping principle of the nearest node in the discrete particle swarm optimization mapping reduces the energy consumption of communication between tasks. An in-depth analysis of the influencing factors of the ice and snow tourism market shows that the per capita disposable income of urban residents and the number of urban residents have a significant impact on the ice and snow tourism market demand. In addition, regression analysis and demand-based forecasting are important methods to analyze the scale and development trend of tourism. At the same time, it shows an important position in the purpose of urban tourism and regional market share so as to provide a basis for decision-making in tourism destination marketing. This paper mainly studies and analyzes the wireless sensor network and further introduces it into dynamic resource allocation and ice and snow tourism, which can promote the continuous development of dynamic resource allocation and ice and snow tourism.

Spatial effects and impact factors of food nitrogen footprint in China based on spatial durbin panel model.

Reactive nitrogen (Nr) has far-reaching advantages and disadvantages on human beings. Nitrogen footprint (NF) is a tool to quantify the use of Nr in the environment. Food nitrogen footprint (FNF) accounts for the largest proportion of the total NF, and the differences between provinces in China exist objectively. In order to explore the spatial correlation and socio-economic driving factors of China's FNF, this paper uses N-calculator tool to calculate the FNF of 30 provinces in China from 2000 to 2018, and uses exploratory spatial data to analyze the spatial correlation and changes of provincial FNF, The driving factors and spatial effects of FNF change in the province were analyzed by using spatial Durbin panel model and spatial regression partial differential method. The results showed that: (1) There is a significant and stable positive spatial dependence and heterogeneity in the FNF among provinces; (2) The direct effect factors of promoting the growth of FNF in the province are urban household Engel coefficient, per capita disposable income of rural residents and rural household Engel coefficient. The main factors of restraining the growth of FNF in the province are wastewater discharge per unit GDP and per capita GDP; (3) the spillover effect is mainly manifested as the negative effect of the increase of urban household Engel coefficient on neighboring provinces, and the spillover effect of per capita disposable income of urban residents and nitrogen fertilizer application rate per unit grain yield on the growth of FNF of neighboring provinces is significant. From the policy level, it is necessary to guide healthy and scientific eating habits, reduce the proportion of meat and fish in the diet structure, reduce the nitrogen fertilizer application per unit grain yield, and improve the efficiency of chemical fertilizer utilization. When formulating relevant policies, government departments should give consideration to the cooperation between provincial and regional governments.

Study on the Factors Influencing the Price Volatility of Agricultural Products in China

As a major country in the production and consumption of agricultural products, the price of agricultural products in China occupies an important position in the market price system. The fluctuation of agricultural product prices not only affects the development of national agricultural production, but also affects the growth trend of the national economy. This paper analyzes the reasons for the price fluctuations of agricultural products from three levels of supply, demand and international, and uses the grey relational analysis and VAR model to dynamically analyze the six main factors affecting the price fluctuations of agricultural products in China from 1978 to 2020. The study finds that there is a strong correlation between each influencing factor and the price of agricultural products, among which the consumer price index has the highest correlation with the price of agricultural products. At the same time, the per capita disposable income of urban residents and the consumer price index of urban residents have a positive relationship with the price of agricultural products, the price index of agricultural production means and the exchange rate index have a negative relationship with the price of agricultural products in the short term, and the output of grain and the price of agricultural products have a positive relationship in the short term. The relationship between GDP and agricultural product prices is not obvious.

长江三角洲城市群“三生”功能耦合协调时空分异及其影响因素

PDF HTML阅读 XML下载 导出引用 引用提醒 长江三角洲城市群“三生”功能耦合协调时空分异及其影响因素 DOI: 10.5846/stxb202108082175 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 山西省哲学社会科学规划项目（2018B050）；2020年度山西省研究生教育改革（指令性）研究课题项目（2020YJJG159） Spatial-temporal differentiation and influencing factors of coupling coordination of “production-living-ecological” functions in Yangtze River Delta urban agglomeration Author: Affiliation: Fund Project: Philosophy and Social Science Planning Project of Shanxi Province (No. 2018B050) ；Research Project of Shanxi Province Graduate Education Reform (mandatory) in 2020 (No. 2020YJJG159). 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:长江三角洲城市群是中国城市化水平和经济发展水平最高的城市群，其"三生"功能问题和矛盾日益凸显，"三生"功能耦合协调分析是国土空间规划及区域可持续发展的基础。以长江三角洲城市群为研究区，从农业生产、非农业生产、生活水平、生活保障、生态压力和生态保障六个方面筛选31项指标构建"三生"功能评价指标体系，采用熵权法和AHP法组合确定评价指标权重。并引入耦合协调度模型，以2000-2019年为研究时段进行"三生"功能评价及其耦合协调度分析，并运用面板数据模型和Robust回归分析影响研究区"三生"功能的主要因素。结果表明：（1）研究区2000-2019年间生产、生活、生态功能整体上稳步提升，其中，生产功能东西部发展优于中部，低值区缩减；生活功能东部优于西部，南部优于北部；生态功能随时间呈现由西南部到东南部最优的变化特征。"三生"功能总体表现为"东部优于西部，南部优于北部，东南部发展最优"格局，空间差异明显；（2）生产-生活严重失调城市占比由23.08%缩减为0，基本协调城市占比由11.54%提高到46.15%，中度协调城市占比由0提高到53.85%，耦合协调性提高显著；生产-生态中度失调城市占比由57.69%降为4.8%，基本协调城市占比由19.23%提升为88.46%；生活-生态耦合严重和中度失调城市占比由有到无，中度协调城市占比由0提升为88.46%，上海市升为高度协调城市；生产-生活-生态功能耦合协调度逐步提高，在空间上呈现东部、东南部为主要高值区，沿海优于内陆的分布格局；（3）地均农业机械总动力、地均固定资产投资、城镇常住居民人均可支配收入、草地面积、绿地覆盖率等因素对研究区"三生"功能耦合协调发展起到了巨大的推动作用，而农村常住居民人均可支配收入对"三生"功能耦合协调起到了限制作用。研究结果能为其社会经济稳定发展与国土空间资源利用可持续发展提供参考依据。 Abstract:The urban agglomeration in the Yangtze River Delta is the one with the highest level of urbanization and economic development in China. Its "production-living-ecological" function problems and contradictions have become increasingly prominent. The coupling and coordination analysis of "production-living-ecological" functions is the basis of land space planning and regional sustainable development. Taking the Yangtze River Delta urban agglomeration as the research area, 31 indicators were selected from six aspects of agricultural production, non-agricultural production, living standards, living security, ecological pressure and ecological security to construct the evaluation index system of " production-living-ecological " functions. The entropy weight method and AHP method were used to determine the weight of the evaluation index. The coupling coordination degree model was introduced to evaluate the"production-living-ecological " functions and analyze its coupling coordination degree from 2000 to 2019. The panel data model and Robust regression were used to analyze the main factors affecting the "production-living-ecological " functions in the study area.The results show that:(1) The production, living and ecological functions of the study area have improved steadily from 2000 to 2019. Among them, the development of production function in the east and west is better than that in the middle, and the low value area is reduced.; The living function of the east is better than that of the west, and that of the south is better than that of the north.; The ecological function shows the best change characteristics from southwest to southeast over time. The overall performance of ‘production-living-ecological’ functions is ‘the east is better than the west, the south is better than the north, and the southeast is the best’ pattern, with obvious spatial differences; (2) The proportion of cities with severe production-life imbalance decreased from 23.08% to 0, the proportion of cities with basic coordination increased from 11.54% to 46.15%, the proportion of cities with moderate coordination increased from 0 to 53.85%, and the coupling coordination increased significantly;The proportion of cities with moderate production-ecological imbalance decreased from 57.69% to 4.8%, and the proportion of cities with basic coordination increased from 19.23% to 88.46%; the proportion of cities with severe and moderately unbalanced life-ecological coupling ranges from existence to none;the proportion of moderate coordinated cities increased from 0 to 88.46%, and Shanghai increased to highly coordinated cities;The coupling coordination degree of production, living and ecological functions gradually increased. The spatial distribution pattern showed that the eastern and southeastern regions were the main high-value regions, and the coastal regions were better than the inland regions. (3) Factors such as total power of agricultural machinery per land, investment in fixed assets per land, per capita disposable income of urban residents, grassland area, green coverage rate and other factors have contributed to the coordinated development of the "production-living-ecological "functions in the study area,having a huge driving force, and the per capita disposable income of rural residents has restricted the function of production-living-ecological coupling and coordination. The results can provide a reference basis for the stable development of its social economy and the sustainable development of land space resources utilization. 参考文献 相似文献 引证文献

Nonlinear Influence of Public Services on Urban Housing Prices: A Case Study of China

Owing to China’s rapid urbanization and internal migration, public services are unevenly distributed in cities, affecting urban housing prices. This study examines the dynamic effect of China’s public service levels on urban housing prices. We used the entropy method to calculate the public service index of 30 cities in China and a panel threshold regression model to explore the relationship between urban public service levels and housing prices. We found that the degree of the effect of public service levels on urban housing prices varies with the per capita disposable income of urban residents, demonstrating an inverted U-shaped curve. The role of public services in promoting urban housing prices increases with the increase in the level of urbanization. When the level of urbanization exceeds its threshold, the enhancement effect increases. These results help us better understand the theories of housing price changes in Chinese cities and support policymakers in formulating effective control measures for the housing market.