Investment In Fixed Assets Research Articles

基于TOPSIS模型的海南岛土地综合承载力时空变化及障碍度诊断

PDF HTML阅读 XML下载 导出引用 引用提醒 基于TOPSIS模型的海南岛土地综合承载力时空变化及障碍度诊断 DOI: 10.5846/stxb202110283032 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 海南省自然科学基金（421MS057）；三亚学院人才引进项目（USYRC19-19）；国家社会科学基金项目（15BJY025） Spatio-temporal change and obstacle degree diagnosis of comprehensive land carrying capacity in Hainan Island based on TOPSIS model Author: Affiliation: Fund Project: 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:土地是人类一切活动的根本，是区域经济与社会发展的重要保障。为探讨海南岛土地综合承载能力，依据2009-2019年统计数据，采用TOPSIS和GM （1.1）模型从时序角度评价并预测了2020-2030年海南岛土地综合承载力，并借助ArcGIS软件和障碍度模型对各市县2015年、2019的土地综合承载力进行动态分析及障碍度诊断。结果显示，海南岛土地综合承载力主要受经济与社会子系统的影响，2009-2019年土地综合承载力水平虽有波动但整体呈缓慢升高趋势，其中水土资源与生态环境子系统贴近度值表现为下降趋势，而经济与社会子系统贴近度值明显升高。预测结果表明2020-2030年土地综合承载力呈持续上升趋势。土地综合承载力空间动态变化差异显著，总体表现为沿海市县综合承载力水平高于内陆市县，2015年与2019年处于较高水平的是海口和三亚，处于中等水平的2015年为8个市县，2019年达到11个市县，处于较低水平的2015年为8个市县，2019年只有5个市县，并且各市县子系统承载力差异显著。障碍度分析表明，2015年和2019年子系统障碍度最高的是经济子系统，2015年障碍因子主要有经济密度（X9）、地均固定资产投资（X12）、耕地有效灌溉率（X6）及人均GDP （X8）；2019年障碍因子主要有经济密度（X9）、地均固定资产投资（X12）、人均GDP （X8）及复种指数（X14）。经济发展水平是制约各市县土地综合承载力的主要障碍因素。研究将为海南岛自由贸易港建设中生态环境与社会经济可持续发展提供科学依据。 Abstract:Land is the foundation of all human activities and important guarantee for regional economic and social development. In order to explore the comprehensive land carrying capacity of Hainan Island, based on the statistical data from 2009 to 2019, the TOPSIS and GM (1.1) models were used to evaluate and predict the comprehensive land carrying capacity of Hainan Island from 2020 to 2030 from time series perspective. In addition, ArcGIS software and obstacle degree model were used to conduct dynamic analysis and obstacle degree diagnosis of the comprehensive land carrying capacity of cities and counties in 2015 and 2019. The results show that the comprehensive land carrying capacity of Hainan Island is mainly affected by the economic and social subsystems. Although the level of comprehensive land carrying capacity fluctuated from 2009 to 2019, it showed a slow upward trend as a whole. The closeness value of water and soil resources and ecological environment subsystem showed a downward trend, while the closeness value of economic and social subsystem increased significantly. The prediction results show that the comprehensive land carrying capacity shows a continuous upward trend in 2020-2030. There are significant differences in the spatial dynamic changes of the comprehensive land carrying capacity. The overall performance is that the comprehensive carrying capacity of coastal cities and counties is higher than that of inland cities and counties. In 2015 and 2019, Haikou and Sanya were at a high level. Eight cities and counties were at the medium level in 2015, 11 cities and counties in 2019. And 8 cities and counties were at the low level in 2015, while only 5 cities and counties in 2019 and the sub-system carrying capacity of each city and county was significantly different. The analysis of obstacle degree shows that the economic subsystem had the highest obstacle degree in 2015 and 2019. In 2015, the obstacle factors mainly included economic density (X9), fixed asset investment per land (X12), effective irrigation rate of cultivated land (X6) and GDP per capita (X8). In 2019, the main obstacle factors were economic density (X9), fixed asset investment per land (X12), GDP per capita (X8) and multiple cropping index (X14). The level of economic development is the main factor restricting the comprehensive carrying capacity of land in cities and counties. This word is expected to provide the scientific basis for ecological conservation and economic sustainable development in the construction process of Hainan Free Trade Port. 参考文献 相似文献 引证文献

The Influence of the Urban-Rural Income Disparity on the Industrial Structure—Taking the Yangtze River Delta Region as an Example

In this paper, the effect of the mediation effect is mainly used to test and analyze the regression model, and most scholars have studied the impact of the modernization of the industrial structure on the income gap. However, this paper is from another perspective, based on the social background of high-quality development, the main study is the impact mechanism of urban and rural income gap on the industrial structure, taking the Yangtze River Delta as the main research object, and specifically selecting 22 central cities in the Yangtze River Delta region, which is also one of the highlights of this study. The regression model is constructed by using the intermediary effect, and the four intermediary variables of fiscal expenditure (M1), fixed asset investment (M2), number of patent applications (M3), and total import and export (M4) are selected, which represent the role of the government, fixed asset investment, scientific and technological level and opening-up level, and study and analyze the inherent influence mechanism between each variable. Before doing specific research, I consulted the papers and literature of many other outstanding scholars, among which Cheng Yuhong and Cheng Chi’s “The Influence Mechanism of industrial structure of urban and rural income gap” [1] has great reference value for this paper. According to the research results, under the background of high-quality development in the Yangtze River Delta region, the expansion of the income gap between urban and rural areas will inhibit the upgrading of the industrial structure, so it is necessary to focus on building a new type of urbanization, accelerating the construction of an urban innovation system, optimizing the rural employment structure to narrow the income gap between urban and rural areas, and providing impetus for the continuous upgrading of the industrial structure.

Research on the economic development impact of earthquake disaster in China

As one of the areas with frequent earthquake disasters, China’s social stability and sustained and healthy economic development have been profoundly affected for a long time. Based on the two-way fixed effect model and a series of deterministic indicators of economic development, including education level, economic development, financial development, fixed asset investment and permanent population, this paper designs a standard regression equation for estimating growth and uses time series panel data to analyze the impact of earthquake disasters on China’s economic development. The research results show that the earthquake disaster has an insignificant positive impact on China’s GDP. From the point of view of control variables, education level and financial development level have a positive effect on economic development as a whole, but there are certain differences in the degree of influence. The degree of trade openness has a significant impact on GDP, industry and service industries. Moreover, it has a negative impact on agricultural development.

Методика оценки реальных инвестиций с конфигурацией неординарного денежного потока

The methodology for efficiency evaluation of investment projects, concerning the calculation of several key indicators and making a decision on the advisability of project approval, is well-known in scientific spheres. It is based on the algorithm for evaluating portfolio investments, when the investment itself is initially and simultaneous. Further it generates a certain revenue flow to the owner of a security or physical asset. Real investments, such as capital or fixed assets investments are much more complex and diversified in their structure. The cash flow can naturally start with an influx of funds at the very beginning and then finish with the outflow. Frequently, the capital investment itself is not a single way of infusion, that's why the use of standard approaches often leads to a formal absence or, on the contrary, multitude of the internal rent rates and also causes uncertainty and problems with calculations of the payback period for purely mathematical reasons. Net Present Value can be defined by default in any situation, but the Internal Rate of Return specifically serves as the main relative and comparable indicator for both the project developer and potential investors in present conditions. This article offers the alternative algorithm that allows you to review the full-scale financial and economic characteristics of the project, regardless of the cash flow pattern under any circumstances. The divergences between the known and the proposed methodology are minimal, as the author explains us by researching the examples of the "ordinary" projects. Thus, this model can be considered as reasonable for evaluation purposes in comparison with basic methods, which are not intended to provide such an analysis in general. The object of the proposed research is real investment projects with signs of extraordinarity, the goal is to develop methodological approaches for their correct financial and economic evaluation. The methodological base is the apparatus of financial mathematics, the theory of efficiency and the theory of managerial decision-making. The key result is two approaches that always allow to calculate internal rate of return and the exact payback period, regardless of the configuration of the cash flow. The article will be useful primarily to initiators of projects in existing and created production, as well as potential investors in such innovations.

Demand forecast and influential factors of cold chain logistics based on a grey model.

Due to high requirements of storage, operation and delivery conditions, it is more difficult for cold chain logistics to meet the demand with supply in the course of disruption. And, accurate demand forecasting promotes supply efficiency for cold chain logistics in a changeable environment. This paper aims to find the main influential factors of cold chain demand and presents a prediction to support the resilience operation of cold chain logistics. After analyzing the internal relevance between potential factors and regional agricultural cold chain logistics demand, the grey model GM (1, N) with fractional order accumulation is established to forecast future agricultural cold chain logistics demand in Beijing, Tianjin, and Hebei. The following outcomes have been obtained. (1) The proportion of tertiary industry, per capita disposable income indices for urban households and general price index for farm products are the first three factors influencing the cold chain logistics demand for agricultural products in both Beijing and Tianjin. The GDP, fixed asset investment in transportation and storage, and the proportion of tertiary industry are three major influential factors in Hebei. (2) Agricultural cold chain demand in Beijing and Hebei will grow sustainably in 2021-2025, while the trend in Tianjin remains stable. In conclusion, regional developmental differences should be considered when planning policies for the Beijing-Tianjin-Hebei cold chain logistics system.

Regional Distribution and Reconstruction Strategies of New Industrial Spaces at Multiple Spatial Scales in Shandong Province China

New industrial space is a new industrial area dominated by high-tech zone and economic development zone in China. Shandong is the front of China’s reform and opening up, with relatively complete types of new industrial spaces. With the deepening of China’s reform and opening up, these new types of industrial spaces with different backgrounds, different functions and spatial overlapping are in urgent need of multi-scale spatial reconstruction, so as to give play to the advantages of regional policy superposition, to promote industrial development and spatial restructuring, and to improve the industrial and regional competitiveness of Shandong. From four dimensions of scale, structure, dynamics and share, and seven levels of the number of parks, registered enterprises, foreign capital utilization, fixed asset investment, financial revenue, industrial production and its economic benefits, this paper constructs the evaluation index system of new industrial spaces, and classifies the new industrial spaces in Shandong Province at the dual spatial scales of city and county (district) by means of the principal component analysis and cluster analysis. Then, this paper analyzes the dynamic structure of evolution of Shandong’s new industrial spaces from the aspects of national policy, hierarchical government, technological innovation, transportation and information, and explores the reconstruction mechanism of Shandong’s new industrial spaces. Finally, based on the micro perspective of value chain and enterprise analysis, this paper puts forward the reconstruction strategies and corresponding policy measures of Shandong new industrial spaces at multiple spatial scales of province, interlocking metroplis and city.

Empirical Analysis on the Influencing Factors of China's Economic Development Quality Based on Stepwise Regression

This paper selects 10 factors that affect the quality of economic development in China. Based on the data of the National Bureau of Statistics from 2018 to 2020, the key factors affecting the quality of economic development in China are analyzed by stepwise regression method. According to the empirical results, necessary policy suggestions for high-quality economic development are put forward. The empirical results show that the urbanization rate of permanent residents, the disposable income per capita of rural population, and the growth rate of infrastructure fixed asset investment have a significant role in promoting the quality of China's economic development.

Analysis on the Influencing Factors of the Competitiveness of China's Provincial Star Hotel Industry Based on Regression Analysis

This paper selects data in the 2017 China Tourism Statistics Yearbook about 31 provincial-level regions in mainland China, with cluster analysis used to analyzes the differences in the competitiveness of the Star-rated Hotel Industry in China. The overall competitiveness difference is the largest in the east, second in the west, and smallest in the middle; the east is more competitive than the west, the south is more competitive than the north, the coastal provinces are more competitive than the inland provinces, and the economically developed provinces are more competitive than the underdeveloped provinces. This paper analyzes the factors affecting the competitiveness of provincial star-rated hotels. This paper proposes countermeasures such as accelerating regional economic development, increasing the proportion of the tertiary industry, increasing fixed asset investment in accommodation and catering, and expanding the degree of opening up at end.

Analysis of influencing factors of Fiscal revenue in Beijing based on Ridge regression and Lasso regression model

Based on the fiscal revenue and other relevant economic index data of Beijing from 1995 to 2020, this study uses the research methods of Ridge regression and Lasso regression to explore the influencing factors of Beijing’s fiscal revenue. Considering that the traditional linear regression model will produce strong multicollinearity among many variables. Therefore, ridge regression and Lasso regression model were firstly used to reduce the influence of multicollinearity between variables, and then variable selection was carried out. Finally, the two models were compared according to the analysis results, and the optimal analysis model was selected. The results show that compared with ridge regression model, lasso regression model has better goodness of fit, smaller error and better model. The added value of the second industry, power generation, resident population, urban per capita disposable income and total retail sales of social consumer goods has a positive impact on fiscal revenue, and the whole social fixed assets investment, employment in cities and towns, per capita consumption expenditure of urban households is has a certain negative impact on fiscal income level.

Research on the influencing factors of GDP in Guangdong Province based on grey relational analysis

As the most economically developed region in China, Guangdong Province has important guiding significance for the study of the influencing factors of Guangdong Province's economic development. This paper uses the grey correlation method to study the GDP data of Guangdong Province from 2010 to 2020, and conducts an empirical analysis on the relationship between it and the index system composed of indicators such as environment, investment and education. The research shows that the total social fixed asset investment in the indicator system has the highest correlation with the GDP of Guangdong Province, but the correlations corresponding to different indicators are different. According to its conclusion, this paper puts forward corresponding policy suggestions to provide theoretical support and thinking perspective for the economic development of Guangdong Province.

城镇化对新疆土地利用碳排放的影响及其耦合关系

PDF HTML阅读 XML下载 导出引用 引用提醒 城镇化对新疆土地利用碳排放的影响及其耦合关系 DOI: 10.5846/stxb202106061492 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学基金(31760151) Effects of urbanization on carbon emission from land use in Xinjiang and their coupling relationship Author: Affiliation: Fund Project: 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:推进绿色城镇化和发展低碳经济是实现区域可持续发展的关键。运用综合指标法和碳排放模型分别对2000-2018年新疆14个地(州、市)的城镇化水平和土地利用碳排放进行测度,并基于偏最小二乘法和耦合协调度模型对二者的影响机理和耦合关系进行探讨。结果表明:(1)新疆各地(州、市)的新型城镇化水平差异显著,2018年乌鲁木齐市最高(83.43%),克州最低(18.15%),且城镇化的主导类型以人口城镇化→土地城镇化→经济城镇化→社会城镇化的发展顺序转变;(2)新疆土地利用碳效应由负转正,净碳排放量年均增速达7.86×106 t/a,变异系数以2004年为折点,呈倒"V"型变化趋势,2004年后各地(州、市)碳消耗的相对差异逐渐缩小。(3)经济、社会、土地是城镇化影响区域土地利用碳排放的3个重要维度,人均国内生产总值、第二产业增加值、社会消费品零售总额、全社会固定资产投资总额、建成区面积是其中的极重要因素。(4)各地(州、市)城镇化与土地利用碳排放的耦合度、耦合协调度均呈上升趋势,二者具有良好的共振性,且趋于同步发展,表明新疆城镇化发展过程中能源消耗的负向作用日益凸出。最后为提高新疆碳排放效率,促进城镇化绿色发展提出了建议和对策。 Abstract:Promoting green urbanization and developing low-carbon economy are the key to realize the regional sustainable development. This paper uses the comprehensive index method and carbon emission model to measure the urbanization level and carbon emissions from land use in 14 regions (prefectures and cities) in Xinjiang from 2000 to 2018, and uses partial least squares method and coupling coordination model to discuss the influence mechanism and coupling relationship between the urbanization level and carbon emissions from land use. The results show that:(1) there were significant differences in the new urbanization level among different regions (prefectures and cities) in Xinjiang. In 2018, Urumqi had the highest level (83.43%) and Kizilsu Klrgiz Autonomous Prefecture had the lowest level (18.15%). The dominant type of urbanization changed in the order of population urbanization→land urbanization→economic urbanization→social urbanization. (2) The carbon effect of land use in Xinjiang changed from negative to positive, and the average annual growth rate of net carbon emissions reached 7.86×106 t/a. The coefficient of variation took 2004 as a turning point, showing an inverted "V" trend. After 2004, the relative differences in carbon consumption across regions (prefectures and cities) gradually decreased. (3) Economic, social and land urbanization were three important dimensions of urbanization that affect the regional land use carbon emissions. Per capita GDP, the added value of the secondary industry, the total retail sales of social consumer goods, the social fixed-assets investment and the built-up area were the most important factors. (4) The coupling degree and coupling coordination degree of urbanization and carbon emissions from land use in all regions (prefectures and cities) showed an upward trend. Urbanization and carbon emissions from land use had good resonance and tended to develop synchronously, indicating that the negative effect of energy consumption in the development of urbanization in Xinjiang was increasingly prominent. Finally, this paper puts forward suggestions and countermeasures to improve the efficiency of carbon emissions and promote the green development of urbanization in Xinjiang. 参考文献 相似文献 引证文献

BT-to-VAT reform and firm productivity: Evidence from a quasi-experiment in China

China recently initiated a major tax reform to convert business tax to value-added tax (BT-to-VAT reform), which opened up the tax deduction chain between industries. We used difference-in-differences model and an administrative firm-level dataset from 2011 to 2017 to explore the effect of BT-to-VAT reform on productivity. We found that in contrast to control firms, this reform increased the productivity of the treated firms by 14.6% on average. The positive effects tended to be strengthened in private, large-scale, and capital-intensive firms, as well as in firms with tight financing constraints. Moreover, these positive results of the BT-to-VAT reform appeared to be driven by its positive effect on fixed asset investment, R&D expenditure, and specialization. These findings demonstrate the transformation of tax system has multiple economic effects in developing countries.

The effects of the environmental protection tax law on heavily polluting firms in China.

In 2016, China implemented an environmental protection tax (EPTL2016) to promote the transformation and upgrading of heavily polluting industries through tax leverage. Using panel data of China’s listed companies, this study assesses the treatment effects of the EPTL2016 on the transformation and upgrading of heavily polluting firms by incorporating the intermediary role of the financial market. The empirical findings show that the EPTL2016 significantly reduced the innovation investment and productivity of heavily polluting firms but had no significant effect on fixed-asset investment. Additionally, EPTL2016 reduced the supply of bank loans to heavily polluting firms and increased the value of growth options for private enterprises and the efficiency of the supply of long-term loans to heavily polluting firms. Although the environmental policy of EPTL2016 benefits the transformation and upgrading of heavily polluting industries in many aspects, it generally hinders the industrial upgrading because of the reduction of bank loans.

Determinants of Fixed Asset Investment in the Polish Farms

The aim of this study was to determine the factors affecting the level of investment activity of agricultural producers in Poland. Detailed studies included 4309 farms that kept accounts within the Farm Accountancy Data Network (FADN) accounting system in the years 2010–2018. The study uses Person’s linear correlation method, the multiple correlation method, and regression analysis. For the regression analysis, both static and dynamic models were applied. The level of expenditure on agricultural investment varied in the surveyed households and showed an upward trend during the years 2010–2018. Studies have shown that the investment activity of Polish farms largely depends on the possibility of raising funds from European Union programs dedicated, inter alia, to the development of agricultural holdings. The regression analysis demonstrated that the principal factors affecting the level of agricultural investment include: the amount of long-term liabilities, the family income of the farm, and the amount of investment subsidies. Preferential loans are an important parameter in a dynamic investment model. This study suggests that agricultural policy factors should be taken into account to ensure the appropriate development of Polish farms.

Inclusive wealth index measuring sustainable development potentials for Chinese cities

The UN Sustainable Development Goals (SDGs) are the blueprint to achieve a better and more sustainable future. To achieve the goal, tracking progress — not just on a national level, but locally — is crucial to guide future policy development. While sustainability assessment at the national evel is quite advanced in China, similar assessments focusing at the regional or even at the city-level are currently lacking. Here, we advanced the Inclusive Wealth Index (IWI) framework, which is firstly proposed by the United Nations Development Programme, through taking water wealth into account and adjusting the variable based on data availability. Then we investigate the sustainability performance of 210 cities in China in 2016 via the advanced version of the IWI framework. The analysis makes a holistic assessment based on produced, human, and natural capital, as well as considering heterogeneities in economy, social, and environmental conditions across these cities. We find that cities clustered in the eastern parts of China are characterized by high levels of sustainability performance and increasing capacities for sustainability, largely driven by their high quality and quantity of human capital. In comparison, the western cities have a large amount of low-skilled human capital and low levels of produced capital, which determines their low sustainability performance. Cities clustered in the north are heavily dependent on low value-added products and resource-intensive industries. Furthermore, we make projections of the IWI and its three components for different cities from 2020 to 2030, referring to the index systems presented in city planning which describe the development speed of income, education, fixed asset investment, forests etc. In the future, cities in central and western clusters show considerable potential for increasing IWI per capita, whereas cities with a dominant energy sector in the north would face declining capacity for sustainability due to the exhaustion of fossil fuels and raw materials. By fully taking account of and adapting to local circumstances, we tailor-design pathways for different types of cities to grow their sustainability potentials. Those resources-dependent cities in the north could avoid the impending decline by gradually developing their human and produced capital while abandoning their resource dependency. Our study contributes to city-level sustainable development in China through the lens of per capita IWI and the potential future dynamics of changing compositions in their capital.

Spatiotemporal Trends and Driving Factors of Urban Livability in the Yangtze River Delta Agglomeration

With the development of cities, the relationship between cities is becoming closer, and the study of urban livability based on a single city can no longer meet the guidelines and suggestions for urban agglomerations. A scientific evaluation of livability in urban agglomerations can better help cities to recognize the advantages and disadvantages. However, most studies on urban livability focus on its connotation and history and neglect simulations and analyses of the future. Based on the Yangtze River Delta agglomeration, this paper establishes an index system using data from 2011 to 2019 to simulate urban livability from 2020 to 2025 through the ARIMA model and analyzes the historical and future data by using GIS methods. The results show the following: (1) The ARIMA model has good simulation accuracy when applied to urban livability analysis and can provide a reference for future urban livability development. (2) The urban livability of the Yangtze River Delta agglomeration has obviously changed both on the whole and in subsystems. Cities in the upper ranking of livability have developed rapidly, and the difference in urban livability has increased. (3) The spatial autocorrelation of urban livability in the Yangtze River Delta agglomeration is obvious both on the whole and in subsystems. (4) The influencing factors of urban livability development are diverse. The general public budget expenditure for social security and employment, fixed assets investment in municipal public facilities, total retail sales of consumer goods, and education and medical expenditures have positive effects on the development of urban livability, while industrial SO2 emissions have a negative effect. The results show that cities should strengthen inter-city relationships, promote the coordinated development of inter-regional cities, and formulate relevant policies to improve the level of urban environmental governance in the region.

The Impact of Foreign Direct Investment on Income Convergence in China - A Spatial Panel Data Analysis

After taking into account the spatial dependence effects in the panel data consisting of all 31 provinces, direct-controlled municipalities, and autonomous regions in China between the years 1998 and 2017, it found significant spatial autocorrelation effects in both traditional absolute and conditional β income convergence models. At the national level, using the spatial econometric models (Spatial Error Model for absolute convergence and Spatial Durbin Model for conditional convergence), the analysis shows that in the past 19 years from 1999 to 2017, there is no absolute β income convergence. However, there is conditional β income convergence after controlling for all growth factors, while the positive effect of fixed asset investment on regional economic growth is significant, and the effect of population growth is significantly negative. The other growth factors such as FDI inflow, export, and higher education enrollment were surprisingly found no statistically significant effects on regional economic growth. From regional level (Spatial Durbin Model and Spatial Lag Model), there is no conditional β income convergence within each four economic regions. Nonetheless, the northeast region showed an income divergence trend, where only the fixed asset investment is positively significant. This study results imply that China should continue to improve fixed asset investment and control population growth to stimulate regional economic growth and income convergence.

Analysis of influencing factors of carbon emissions in resource-based cities in the Yellow River basin under carbon neutrality target.

In 2020, China promised to achieve carbon peaking by 2030 and carbon neutrality by 2060, and these targets are famous as "Goal 3060" in China. Chinese resource-based cities are concerned about the realization of Goal 3060 to practice national action against environmental change. In this paper, this study evaluates the impact of population, economic growth, energy intensity, industrial structure, fixed asset investment, and urbanization level on carbon emissions in Chinese cities. To do so, the paper divides 36 Chinese cities into four types (growing city, mature city, recessionary city, and regenerative city) from 2003 to 2017 by factor investigation according to the diverse development stages. The extended STIRPAT model is used to assess the impact of various factors on CO2 emissions in the Yellow River basin and diverse city levels. The panel regression analysis was conducted for the basin as a whole and cities at different development stages through a fixed-effects model and a linear regression model with Driscoll-Kraay standard errors. The results show that (1) the total carbon emissions in the Yellow River basin continued to climb during the study period. However, the growth rate slowed down significantly after 2012. In addition, there are differences in the total carbon emissions and growth rate of different cities. (2) Population, real GDP, energy intensity, industrial structure, and fixed asset investment all have a significant positive impact on carbon emissions in the overall basin except the urbanization level which has a significant negative influence on carbon emissions. (3) There is heterogeneity in the influencing factors of carbon emissions in resource-based cities at various development stages. Based on these results, corresponding policies are proposed for different types of cities to help resource-based cities achieve the 3060 dual carbon goal.

Factors Affecting Wind Power Efficiency: Evidence from Provincial-Level Data in China

As a significant energy consumer, China is under tremendous pressure from the international community to address climate change issues by reducing carbon emissions; thus, the use of clean energy is imperative. Wind power is an essential source of renewable energy, and improving the efficiency of wind power generation will contribute substantially to China’s ability to achieve its energy-saving and emission reduction goals. This paper measured the wind power efficiency of 30 provinces in China from 2012 to 2017 using the data envelopment analysis (DEA) method. Moran’s I index and the spatial Durbin model were applied to analyse the spatial distribution of the wind power efficiency and the spatial effects of influencing factors. The results show obvious differences in the spatial distribution of wind power efficiency in China; specifically, the wind power efficiency in the eastern and western regions is higher than that in the central areas. Moreover, wind power efficiency has a significant positive spatial correlation between regions: the eastern and western regions show certain high-high clustering characteristics, and the central area shows certain low-low clustering characteristics. Among the influencing factors, the fixed asset investment and carbon emission intensity of the wind power property have a negative impact on the efficiency of regional wind power production, while the urbanization process and carbon emission intensity have significant spatial spillover effects. The optimization of the economic structure, technological innovation and the construction of energy infrastructure are expected to improve the regional wind power efficiency. The results present a new approach for accurately identifying the spatial characteristics of wind power efficiency and the spatial effects of the influencing factors, thus providing a reference for policymakers.

High-speed railways and local economic performance: evidence from China’s prefecture-level cities

PurposeThe purpose of this paper is to identify the causal effect of high-speed railways (HSRs) and investigate the affecting channels; the second purpose is to examine how HSRs change the distribution of economic activity across cities and sectors.Design/methodology/approachA difference-in-difference strategy is implemented to estimate the impact of recently built HSRs on local economic performance in China, exploiting the geography and time variations in HSR operations.FindingsUsing panel data from China’s City Statistical Yearbook 2001–2019, the authors find that HSRs lead to a significant increase in cities’ gross domestic product (GDP) and GDP per capita, but the authors do not find any significant change in GDP growth. This conclusion still holds true after the authors address the endogeneity problems. A mechanism analysis shows that HSRs improve local economic performance mainly by increasing fixed asset investment. The authors also find that the HSR investment is a policy that favors metropolitan areas due to the larger increase in the GDP for larger cities and with HSRs, the industrial and service sectors will further agglomerate in larger cities.Originality/valueThe authors contribute to the literature in several ways. First, this paper improves the estimation strategy in identifying the HSR impact on the local economic performance. Second, this paper investigates the affecting channels of HSRs. This paper proves that HSRs in China promote the cities’ economic performance mainly by increasing the fixed asset investment. Third, this study provides evidence for the new economic geography models pioneered by Krugman (1991).