scholarly journals Corruption, Hidden Economy and Environmental Pollution: A Spatial Econometric Analysis Based on China’s Provincial Panel Data

2019 ◽  
Vol 16 (16) ◽  
pp. 2871 ◽  
Author(s):  
Shi Wang ◽  
Yizhou Yuan ◽  
Hua Wang
Keyword(s):  
Panel Data ◽  
Environmental Pollution ◽  
Environmental Quality ◽  
Spatial Econometrics ◽  
Interaction Effect ◽  
Spatial Econometric ◽  
Hidden Economy ◽  
Pollutant Discharge ◽  
And Control ◽  
The Impact

Previous studies show that the environmental quality is significantly influenced by corruption and the hidden economy separately. However, what is the impact of their interaction effect on environmental quality? Based on Multiple Indicators Multiple Causes (MIMIC) model, this study calculates the scale of hidden economy in Chinese provinces firstly. Then, we apply the method of spatial econometrics to analyze the interaction effect of corruption and the hidden economy on environmental pollution with China’s provincial panel data from 1998 to 2017. The results indicate that the interaction effect between corruption and hidden economy significantly increases pollutant discharge, suggesting that both anti-corruption and control of the hidden economy may improve environmental quality directly and indirectly.

scholarly journals The Impact of Foreign Direct Investment on Environmental Pollution in China: Corruption Matters

2020 ◽  
Vol 17 (18) ◽  
pp. 6477
Author(s):  
Shi Wang ◽  
Hua Wang ◽  
Qian Sun
Keyword(s):  
Foreign Direct Investment ◽  
Environmental Pollution ◽  
Interaction Effect ◽  
Direct Investment ◽  
Econometric Model ◽  
Spillover Effect ◽  
Eastern Region ◽  
Environmental Standards ◽  
Spatial Econometric ◽  
The Impact

This research investigates the interaction effect between corruption and foreign direct investment (FDI) on environmental pollution by applying the spatial econometric model to the panel data of China’s 29 provinces from 1994 to 2015 and analyzes the differences between China’s eastern, central and western regions. Results show that (a) FDI inflow deteriorates the environmental quality, validating the pollution haven hypothesis (PHH); (b) by weakening the environmental standards, corruption enables the inflow of low-quality FDI, weakens the spillover effect of FDI and indirectly causes further environmental pollution; (c) the interaction effect between corruption and FDI on environmental pollution is less significant in the eastern region than in the central and western regions.

scholarly journals The impact of human capital on the economic growth of Vietnam’s cities and provinces: a spatial econometrics approach

2020 ◽  
Vol 4 (1) ◽  
pp. First
Author(s):  
Nguyen Van Si ◽  
Le Trung Kien
Keyword(s):  
Economic Growth ◽  
Human Capital ◽  
Panel Data ◽  
Spatial Econometrics ◽  
Positive Impact ◽  
Spatial Econometric ◽  
Investment Capital ◽  
Total Investment ◽  
Per Capita ◽  
The Impact

Human capital is crucial for national economic growth and for local economic growth as well. In an attempt to investigate the effect of human capital on the economic growth in Vietnam’s cities and provinces, the author adopts spatial econometric models of SDM, SAR, SEM for panel data. Human capital is measured by regular expenditure on education and numbers of trained labors in each province/city. The data used in this study is obtained from the Statistical Yearbook of 63 provinces published by the General Statistics Office in the period of 2010 - 2017. The results show that the SDM model for panel data is more suitable than the SAR, SEM models for research data. Moreover, the gross output per capita of a province/city is not only affected by its regular expenditure on education but also by that of neighboring provinces/cities. GDP per capital of a province/city is also affected by the GDP of its neighboring provinces/cities. In addition, control variables such as total investment capital, population size, provincial competitiveness index of local or neighboring provinces also exert a positive impact on the GDP per capita of a province/city. The influence of trained labor on the economic growth of a province/city has not been found.

scholarly journals Environmental Effects of Credit Allocation Structure and Environmental Expenditures: Evidence from China

2021 ◽  
Vol 13 (11) ◽  
pp. 5865
Author(s):  
Qiming Yang ◽  
Jun He ◽  
Ting Liu ◽  
Zhitao Zhu
Keyword(s):  
Environmental Pollution ◽  
Environmental Quality ◽  
Spatial Data ◽  
Environmental Governance ◽  
Econometric Model ◽  
Private Enterprises ◽  
Spatial Econometric ◽  
Credit Allocation ◽  
Ecological Protection ◽  
Environmental Expenditures

This article studies how the allocation structure of bank credit capital between state-owned and private enterprises and government environmental expenditures affect environmental pollution in China. The present literature argues that credit allocation and government environmental expenditures may play an important role in environmental quality improvement. However, these studies rarely consider the credit allocation structure between State-owned enterprises (SOEs) and private enterprises; in addition, they overlook the interaction effects of credit allocation and government environmental expenditures. Based on these, we put forward three hypotheses. Moreover, the study applies relevant spatial data for 2011–2017 from 31 provinces in China to a spatial econometric model, and the results indicate that (1) environmental pollution among provincial regions shows a significant positive spatial autocorrelation. (2) Environmental expenditures and environmental pollution display an inverse U-shaped relationship, which supports the numerical simulation results. (3) The interaction effect of credit allocation structure and environmental expenditures on environmental pollution is significantly positive, which means that the allocation of more credit capital to private enterprises will restrain the effect of government environmental expenditures. With the increasing significance of environmental protection in China, it is necessary to strengthen the supervision of private enterprises’ environmental pollution behavior, expand government expenditures on ecological protection, and promote regional collaborative environmental governance to improve environmental quality.

Aquatic Environmental Quality: Toxicology

1976 ◽  
Vol 33 (11) ◽  
pp. 2671-2688 ◽  
Author(s):  
R. D. Hamilton
Keyword(s):  
Environmental Quality ◽  
Toxic Chemicals ◽  
Aquatic Environments ◽  
Specific Research ◽  
Research Programs ◽  
And Control ◽  
The Impact ◽  
Canadian Research

Canadian research and control activities regarding the impact of toxic chemicals on aquatic environments are reviewed. Evaluation of specific research programs or results is not treated but an attempt is made to raise and discuss issues common to the problems posed by the use of toxic chemicals.

scholarly journals Statistical Analysis on the Effect of the Utilization of Mineral Resources on the Environmental Impact in China

2021 ◽  
Vol 13 (15) ◽  
pp. 8462
Author(s):  
Wenqi Zhu ◽  
Kangkang Zhang ◽  
Deyi Xu ◽  
Ziyuan Liu ◽  
Jingke Gao
Keyword(s):  
Environmental Pollution ◽  
Environmental Regulation ◽  
Pollution Control ◽  
Technological Progress ◽  
Industrial Structure ◽  
Mineral Resources ◽  
Spatial Econometric ◽  
Synergistic Mechanism ◽  
Technological Level ◽  
The Impact

Based on the spatial econometric model, this paper mainly studies the impact of the utilization of mineral resources on environmental pollution and the impact of environmental regulation on the utilization of mineral resources in 30 provincial regions from 2003 to 2016, and analyzes the impact mechanism of heterogeneity and synergy. The results show that the utilization of mineral resources intensifies the degree of environmental pollution and the degree of economic spatial agglomeration, while environmental regulation can effectively restrain the utilization of mineral resources in the region and the near adjacent areas. Through the analysis results of synergistic mechanism, it can be seen that the improvement of industrial structure alleviates the impact of the utilization of mineral resources on environmental pollution and the restraining effect of environmental regulation on it. The improvement of technological progress has improved the environmental pollution caused by the utilization of mineral resources in this area, but intensified the environmental pollution degree of the utilization of mineral resources in neighboring areas. In the current technological level, the neighboring areas will consume more mineral resources to meet a certain demand, thus aggravating the environmental pollution of the utilization of mineral resources in the neighboring areas. The enhanced intensity of government management significantly improves the pollution control efficiency of environmental regulation on the utilization of mineral resources.

scholarly journals Statistical Analysis of Environmental Pollution Impact on Population Morbidity in the Republic of Mari El

2020 ◽  
Vol 17 (3) ◽  
pp. 58-66
Author(s):  
P. A. Korotkov ◽  
A. B. Trubyanov ◽  
A. A. Avdeeva ◽  
A. I. Gismieva
Keyword(s):  
Public Health ◽  
Panel Data ◽  
Environmental Pollution ◽  
Correlation Coefficients ◽  
Pollution Index ◽  
Morbidity Rate ◽  
Effect Model ◽  
The Republic ◽  
The Impact ◽  
First Time

The article considers an econometric approach to the analysis of relation between the population morbidity rate depending on ecology and the environmental pollution index. Panel data are used in this approach.The purpose is to find quantitative relations between the state of the environment and public health under the differentiated man-caused load threatening public health in the Republic of Mari El. Materials and methods. The research methods are based on the approaches to correlation and regression analysis of the panel data. In order to identify the environmental pollution index statistically related to the morbidity rate, Pearson and Spearman's correlation coefficients were calculated. Then the regression models for the panel data were developed: a fixed-effect model and a random-effect model. The sources of the panel data are the following: Regional Statistics Office in the Mari El Republic (Maristat), Office of the Federal Service for Surveillance on Consumer Rights Protection and Human Wellbeing in the Mari El Republic (Rospotrebnadzor) and Ministry of Healthcare of the Mari El Republic. The data include six air and water pollution indexes and seven priority indicators of the population morbidity rate in 15 municipal districts of the Mari El Republic in the period of 2009–2017.Results. The analysis of the Pearson and Spearman's correlation coefficients helped to identify environmental pollution indexes closely related to the population morbidity rate. These indicators were used as input data of the panel regression model. Three statistically significant panel regression models were identified. They describe the impact of pollution of drinking water from the distributed network on bronchial asthma morbidity among 0–14-aged children diagnosed for the first time in their life; and the impact of emission into the atmosphere of pollutants from the point emission sources on gastritis and duodenitis morbidity among 15–17 aged teenagers diagnosed for the first time in their life.Conclusion. The identified models have biological plausibility. The ethiopathogenetic analysis confirms the possibility of existence of the identified relations. The statistically significant relations between environmental pollution and public health do not prove existence of cause-and-effect links between them. It is statistical demonstration of the hypothesis of their possible existence. This demonstration is an essential work stage to make the hypothesis a hard fact. In the future, it is proposed to use additional, more objective and integral evaluation of environmental quality, for example, the fluctuating asymmetry of bilateral features of biological objects.

Same Trade Openness Yet Different Environmental Quality — But Why?

2020 ◽  
Vol 11 (01) ◽  
pp. 2050002
Author(s):  
Shu-Chen Chang ◽  
Hsiao-Fen Chang
Keyword(s):  
Environmental Pollution ◽  
Environmental Quality ◽  
Threshold Model ◽  
Trade Openness ◽  
Threshold Effect ◽  
Pollutant Emissions ◽  
Negative Effects ◽  
Threshold Test ◽  
Alternative Measures ◽  
The Impact

This paper re-studies the relationship between trade openness and environmental pollution. Through the theoretical framework, there is a non-uniform effect of trade openness on environmental pollution. Utilizing four alternative measures of trade openness as threshold variables, this paper examines the effect of trade openness on environmental pollution. We adopt a regression with nonlinearity, in which our nonlinear model includes two regressions — a threshold model and an interaction-term model. Utilizing four alternative measures of trade openness, our threshold test shows a single-threshold effect on pollutant emissions, implying that there are two regimes: low- and high-corruption. Our empirical results show that for countries with high-corruption, increases in trade openness significantly reduce pollutants emissions whatever CO2 emissions or SO2 emissions, and the larger effects of trade openness on environmental quality. However, the impact of trade openness on pollution was not found in countries with low-corruption. This study suggests that further trade openness and reduced environmental degradation (i.e., decline in CO2 and SO2 emissions) are compatible rather than competing objectives, especially in high-corruption countries. Furthermore, our results also show that in low-corruption countries, the negative effects of income on CO2 emissions are statistically significant, but in high-corruption countries it is not so.

scholarly journals Nonlinear Influence of Chinese Real Estate Development on Environmental Pollution: New Evidence from Spatial Econometric Model

2022 ◽  
Vol 19 (1) ◽  
pp. 588
Author(s):  
Wenqin Gong ◽  
Yu Kong
Keyword(s):  
Real Estate ◽  
Environmental Pollution ◽  
Econometric Model ◽  
Real Estate Development ◽  
Real Estate Industry ◽  
Spatial Econometric ◽  
The Real ◽  
The Real Estate ◽  
Spatial Econometric Model ◽  
The Impact

Environmental pollution is a problem of universal concern throughout the globe. The development of real estate industry not only consumes huge resources, but also has close ties with high-consumption industries such as the construction industry. However, previous studies have rarely explored the impact of real estate development on environmental pollution. Therefore, this paper employs the entropy method to construct a comprehensive index of environmental pollution based on panel data of 31 provinces in China from 2000 to 2017, and empirically examines the impact of real estate development on environmental pollution. This article uses real estate investment to measure the development of the real estate industry. In view of the high spatial autocorrelation of environmental pollution, this paper selects a spatial econometric model. The empirical study found that: (1) By using the Spatial Durbin Model, real estate development has an inverted U-shaped impact on environmental pollution. Meanwhile, most cities have not yet reached the turning point; that is, with the continuous development of the real estate industry, environmental pollution will continue to increase. (2) Further regional heterogeneity found that the inverted U-shaped relationship still exists in coastal and inland areas. (3) Finally, this article used the Spatial Mediation Model to explain the nonlinear impact of real estate development on environmental pollution, with two important mediating variables: population density and industrial structure. Through the above analysis, it can be observed that real estate development has a significant impact on environmental pollution. Thus, the country and the government can reduce environmental pollution by improving the investment structure, using environmentally friendly building materials, guiding population flow and promoting industrial upgrading.

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