scholarly journals Convergence Study of Water Pollution Emission Intensity in China: Evidence From Spatial Effects

2021 ◽  
Author(s):  
Yixuan Han ◽  
Nan Li ◽  
Hailin Mu ◽  
Rong Guo ◽  
Rongkang Yao ◽  
...  
Keyword(s):  
Water Pollution ◽  
Spatial Autocorrelation ◽  
Emission Intensity ◽  
Industrial Structure ◽  
Development Economic ◽  
Spatial Effects ◽  
Promoting Effect ◽  
Local Conditions ◽  
Pollution Emission ◽  
Pollution Emissions

Abstract One of the challenges that China currently faces is how to reduce the emissions of the water pollution. However, the study of water pollution convergence has certain policy significance for controlling the emissions of water pollution. This article firstly uses chemical oxygen demand（COD）and ammonia nitrogen（NH3-N）as indicators of water pollution. Due to the obvious spillover effect of water in space, this article adds spatial effect to the convergence model. Based on panel data of 30 provinces and cities from 2006 to 2017, this article uses a dynamic spatial Dubin model to analyze the convergence of water pollution emission intensity to address the endogenous problem in the model. The empirical results of this paper show that there is absolute β-convergence and conditional β-convergence in the intensity of water pollution emissions. The spatial autocorrelation test shows that there is a positive spatial autocorrelation of water pollution emissions, which means that the pollution emissions in neighboring areas will affect the emissions in the local area. The industrial structure has a certain promoting effect on the emission of water pollution, which means that adjusting the industrial structure and alleviating the structure of the secondary industry is the trend of future development. Economic growth can curb the emissions of water pollution. The influences of urbanization and foreign investment on the emissions of the two pollutants are inconsistent, and policies can be formulated according to local conditions in the future.

scholarly journals The Environmental Effects of International Trade in China: Measuring the Mediating Effects of Technology Spillovers of Import Trade on Industrial Air Pollution

2021 ◽  
Vol 13 (12) ◽  
pp. 6895
Author(s):  
Shiyue Zhang ◽  
Alan R. Collins ◽  
Xiaoli L. Etienne ◽  
Rijia Ding
Keyword(s):  
Air Pollution ◽  
Technological Innovation ◽  
Industrial Structure ◽  
Technology Spillovers ◽  
Mediating Effects ◽  
Industrial Air Pollution ◽  
Pollution Emission ◽  
Pollution Emissions ◽  
Import Trade ◽  
Air Pollution Emissions

China is in a strategic phase of an industrial green transformation. Industrial air pollution is a key environmental target for governance. Because import trade is a core channel through which advanced environmental protection technology is absorbed, the question of whether technology spillovers brought about by import trade can reduce industrial air pollution emissions is a topic worth exploring. This paper uses a generalized spatial two-stage least-square (GS2SLS) model to explore the impact of import trade technology spillovers on industrial air pollution emission intensities using panel data from 30 provinces and cities between 2000 and 2017. Economic scale, industrial structure, and technological innovation are used as intermediary variables to test whether they play mediating effects. The results show that: (1) capital and intermediate goods technology spillovers directly reduce industrial air pollution emission intensity and (2) import trade technology spillovers indirectly reduce emission intensities by expanding economic scale, optimizing industrial structure, and enhancing technological innovation through mediating variables. Furthermore, industrial structure optimization and technological innovation have the largest mediating effects on industrial SO2, while economic expansion has the most significant mediating effect on industrial smoke and dust. The mediating effects of technology spillovers from intermediate goods exceed those of capital technology spillovers. Finally, industrial air pollution emission intensity demonstrates both spatial agglomeration and time lag effects. Environmental regulations and energy structure are shown to increase industrial air pollution emissions, while urbanization and foreign direct investment reduce industrial air pollution. Based upon these research results, some pertinent policy implications are proposed for China.

Off-office audit of natural resource assets and water pollution: a quasi-natural experiment in China

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Xiaowei Ma ◽  
Muhammad Shahbaz ◽  
Malin Song
Keyword(s):  
Water Pollution ◽  
Big Data ◽  
Water Resources ◽  
Natural Resource ◽  
Prevention And Control ◽  
Industrial Structure ◽  
Dynamic Effect ◽  
Content Type ◽  
Audit System ◽  
And Control

PurposeThe purpose of this paper is to analyze the impact of the off-office audit of natural resource assets on the prevention and control of water pollution against a background of big data using a differences-in-differences model.Design/methodology/approachThis study constructs a differences-in-differences model to evaluate the policy effects of off-office audit based on panel data from 11 cities in Anhui Province, China, from 2011 to 2017, and analyzes the dynamic effect of the audit and intermediary effect of industrial structure.FindingsThe implementation of the audit system can effectively reduce water pollution. Dynamic effect analysis showed that the audit policy can not only improve the quality of water resources but can also have a cumulative effect over time. That is, the prevention and control effect on water pollution is getting stronger and stronger. The results of the robustness test verified the effectiveness of water pollution prevention and control. However, the results of the influence mechanism analysis showed that the mediating effect of the industrial structure was not obvious in the short term.Practical implicationsThese findings shed light on the effect of the off-office audit of natural resource assets on the prevention and control of water pollution, and provide a theoretical basis for the formulation of relevant environmental policies. Furthermore, these findings show that the implementation of the audit system can effectively reduce water pollution, which has practical significance for the sustainable development of China's economy against the background of big data.Originality/valueThis study quantitatively analyzes the policy effect of off-office auditing from the perspective of water resources based on a big data background, which differs from the existing research that mainly focuses on basic theoretical analysis.

scholarly journals Integrated Transport Efficiency and Its Spatial Convergence in China’s Provinces: A Super-SBM DEA Model Considering Undesirable Outputs

2018 ◽  
Vol 8 (9) ◽  
pp. 1698 ◽  
Author(s):  
Fei Ma ◽  
Wenlin Wang ◽  
Qipeng Sun ◽  
Fei Liu ◽  
Xiaodan Li
Keyword(s):  
Spatial Autocorrelation ◽  
Traffic Accidents ◽  
Central Zone ◽  
Data Envelopment Analysis Model ◽  
Undesirable Outputs ◽  
Spatial Effects ◽  
Analysis Model ◽  
Growth Trend ◽  
Transport Efficiency ◽  
Transport Industry

Undesirable outputs, such as carbon emissions and loss of property due to traffic accidents, hold great significance for the sustainable development of the transport industry. In this study, we applied a super-efficiency data envelopment analysis model with a slack-based measure (Super-SBM DEA) considering undesirable outputs to measure the integrated transport efficiency (ITE) of 31 provinces in China during the period of 2009–2016. Following this, we used a spatial autocorrelation model to test and verify the spatial autocorrelation of the ITEs at the level of the 31 provinces, and further to explore the aggregating features. Finally, considering the spatial effects that emerged, we constructed a β-convergence model to analyze the convergence characteristics of China’s ITEs and investigate its conditional factors. The research results show that the average ITE demonstrated a linear growth trend; the effective decision-making units (the ITE value was greater than 1) are only 11 provinces, accounting for about 35% by 2016. The mean of ITEs was also found to present a law of decreasing order of Eastern, Central and Western Zones. However, the Central Zone and Western Zone have a better efficiency improvement trend compared to the Eastern Zone. The Moran’s I index was bigger than zero, indicating that the ITEs formed a spatial autocorrelation phenomenon. The Moran scatter plots further showed that the provincial ITEs mainly followed the patterns of high–high, high–low and low–low aggregation. The ITE of the 31 provinces was found to have a clear absolute β-convergence and conditional β-convergence characteristics. Moreover, the level of economic development, household per capita traffic consumption, transport industry scale, technology advancement and transport intensity were all seen to have an important impact on the convergence of integrated transport efficiency. It is hoped that the findings of this study may contribute further insights and practical knowledge to effectively measuring the development level of China’s integrated transport efficiency, and to understanding future changes in the ITE gap among Chinese provinces.

Political incentives, Party Congress, and pollution cycle: empirical evidence from China

2020 ◽  
pp. 1-17
Author(s):  
Zhihua Tian ◽  
Yanfang Tian
Keyword(s):  
Environmental Pollution ◽  
Emission Intensity ◽  
The Political ◽  
Incentive Structure ◽  
Pollution Emission ◽  
Political Incentives ◽  
Before And After ◽  
Local Officials ◽  
The Difference ◽  
The Impact

Abstract The political incentives of local officials affect their preferences for policy options. This study examines the impact of the convening cycle of Provincial Communist Party Congresses (PCPCs) in China on pollution emission intensity. Based on the data of 281 cities and city officials from 2003 to 2014, the present study finds strong evidence of a political pollution cycle manifesting as significant increases in pollution emission intensity before PCPCs followed by visible decreases after PCPCs. PCPCs provide city officials with strong political incentives to pursue short-term economic performance before congresses, which leads to a surge in pollution emission intensity. The difference in pollution emission intensity before and after the PCPCs reveals the existence of such political incentives. The findings suggest that a significant relationship exists between the political incentives of city officials and environmental pollution. Therefore, the effective governance of environmental pollution must involve changing the incentive structure of city officials.

scholarly journals The Effects of Releasing Greenbelt Restrictions on Land Development in the Case of Medium-Sized Cities in Korea

2019 ◽  
Vol 11 (3) ◽  
pp. 630 ◽  
Author(s):  
Jae Ik Kim ◽  
Jun Yong Hyun ◽  
Seom Gyeol Lee
Keyword(s):  
Urban Growth ◽  
Metropolitan Areas ◽  
Satellite Image ◽  
Land Development ◽  
Spatial Effects ◽  
Local Conditions ◽  
Attribute Data ◽  
Growth Policy ◽  
Urban Problems ◽  
Do So

Many metropolitan areas around the world aim to control urban growth with a view to achieving efficiency and containing urban problems. Among many urban growth policy tools, the green belt (GB) policy is known as the most rigid and strongest. However, there has been no study on the consequences when GB restrictions are completely removed. The primary purpose of this study is to analyse the spatial effects of greenbelt removal on land development in Korea’s medium-sized cities between 2000 and 2017. To do so, we used the Landsat thematic mapper (TM) 5 satellite image (2000) and Landsat OLI TIRS 8 satellite image (2017) along with various attribute data to model the spatial effects of greenbelt removal in the cases of three medium-sized cities in Korea. The result of difference-in-difference (DID) analysis confirms that the effects of GB removal on land development vary depending on the local conditions of land development.

Spatial Effects and Ecological Inference

2002 ◽  
Vol 10 (3) ◽  
pp. 276-297 ◽  
Author(s):  
Luc Anselin ◽  
Wendy K. Tam Cho
Keyword(s):  
Data Analysis ◽  
Spatial Autocorrelation ◽  
Random Coefficient ◽  
Parameter Estimates ◽  
Spatial Effects ◽  
Ecological Inference ◽  
Simulation Experiments ◽  
Coefficient Variation ◽  
Inference Methods

This paper examines the role of spatial effects in ecological inference. Both formally and through simulation experiments, we consider the problems associated with ecological inference and cross-level inference methods in the presence of increasing degrees of spatial autocorrelation. Past assessments of spatial autocorrelation in aggregate data analysis focused on unidimensional, one-directional processes that are not representative of the full complexities caused by spatial autocorrelation. Our analysis is more complete and representative of true forms of spatial autocorrelation and pays particular attention to the specification of spatial autocorrelation in models with random coefficient variation. Our assessment focuses on the effects of this specification on the bias and precision of parameter estimates.

scholarly journals Foreign Trade, FDI and the Upgrading of Regional Industrial Structure in China: Based on Spatial Econometric Model

2020 ◽  
Vol 12 (3) ◽  
pp. 815 ◽  
Author(s):  
Shan-Li Wang ◽  
Feng-Wen Chen ◽  
Bing Liao ◽  
Cuiju Zhang
Keyword(s):  
Foreign Trade ◽  
Industrial Structure ◽  
Econometric Model ◽  
Spillover Effect ◽  
Spatial Effects ◽  
Spatial Agglomeration ◽  
Significance Level ◽  
Spatial Spillover ◽  
Spatial Spillover Effect ◽  
Regional Industrial Structure

The upgrading of industrial structure is the core means of coordinating economic development and environment protection. Its spatial agglomeration can also reduce environmental pollution partly. The upgrading of China’s industrial structure has become an important issue concerned by the whole society. To better understand this issue, based on the provincial data of China (1997–2017), this paper strives to explore the spatial effects of foreign trade and foreign direct investment (FDI) on the upgrading of China’s regional industrial structure by constructing the weight matrix of economic distance, and by introducing the spatial autocorrelation analysis method and spatial panel econometric model. The results show that: 1. The Moran’s I index of China’s import, export, FDI, and industrial structure upgrading has passed the 5% significance level test, displaying remarkable spatial agglomeration characteristics. 2. Foreign trade and FDI are important driving factors to upgrade China’s industrial structure. 3. Foreign trade has a significant spatial spillover effect. Imports and exports can not only promote the upgrading of local industrial structure, but also radiate to other regions, promote or inhibit the development of its industry, and further affect the national data. 4. The spatial spillover effect of FDI is not significant. Finally, some policy suggestions are put forward.

Reflections on Improving Emission Reduction of Key Pollutants in Jingdezhen

2014 ◽  
Vol 722 ◽  
pp. 405-408
Author(s):  
Jie Huang ◽  
Jing Kun Zhou
Keyword(s):  
Air Pollution ◽  
Emission Reduction ◽  
Industrial Structure ◽  
Current Situation ◽  
Capacity Control ◽  
Clean Production ◽  
The Past ◽  
Pollution Emissions ◽  
And Control ◽  
Total Discharge

As Ceramics Capital of China, Jingdezhen had very serious air pollution in the past. In recent ten years, through strengthened management and other means, the total discharge of pollutants has been reduced significantly. The article briefly describes the current situation of Jingdezhen City’s emission reduction work, analyzes its challenges in emission reduction and gives several suggestions for improving Jingdezhen City’s emission reduction work, for example, Jingdezhen City shall vigorously promote clean production, reduce production pollution intensity, resolutely eliminate backward technology and capacity, control pollution emissions of new-built projects, realize supervision and control, strengthen leadership, optimize industrial structure, enhance structural emission reduction and so on.

scholarly journals Spatial Spillover of House Prices: An Empirical Study of the Yangtze Delta Urban Agglomeration in China

2019 ◽  
Vol 11 (2) ◽  
pp. 544 ◽  
Author(s):  
Ling Zhang ◽  
He Wang ◽  
Yan Song ◽  
Haizhen Wen
Keyword(s):  
Indirect Effects ◽  
Spatial Dependence ◽  
Industrial Structure ◽  
House Prices ◽  
Urban Agglomeration ◽  
Spatial Effects ◽  
Yangtze Delta ◽  
Data Set ◽  
Section Data ◽  
Year 2000

This study investigates the spatial dependence of house prices in the Yangtze Delta Urban Agglomeration since the year 2000. According to Moran’s I index and the LISA scatter plot derived from a cross-section data set, the spatial dependence of house prices can be traced across the 25 cities in the agglomeration and became more evident after 2005. This study develops a spatial panel model with geographical distance and economic distance weight matrices. Spatial effects significantly influenced house prices in both cases but the intensity of the former was weaker than for the latter. Income, proportion of the tertiary industry, and amenity exhibited significant indirect effects on house prices in other cities in the inner region of the agglomeration, while competition of population between cities with economic proximity exerted negative indirect effects. Furthermore, urban industrial structure, innovation capability, and urbanization degree revealed differences in terms of spatial dependence among various city groups.

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