scholarly journals Spatio-Temporal Effects of Multi-Dimensional Urbanization on Carbon Emission Efficiency: Analysis Based on Panel Data of 283 Cities in China

2021 ◽  
Vol 18 (23) ◽  
pp. 12712
Author(s):  
Zhanhang Zhou ◽  
Linjian Cao ◽  
Kuokuo Zhao ◽  
Dongliang Li ◽  
Ci Ding
Keyword(s):  
Panel Data ◽  
Spatial Heterogeneity ◽  
Carbon Emission ◽  
Negative Impact ◽  
Low Carbon ◽  
Promoting Effect ◽  
Gradual Improvement ◽  
Emission Efficiency ◽  
Spatio Temporal ◽  
The Impact

Under the influence of complex urbanization, improving the carbon emission efficiency (CEE) plays an important role in the construction of low-carbon cities in China. Based on the panel data of 283 prefectural-level cities in China from 2005 to 2017, this study evaluated the CEE by the US-SBM model, and explored the spatial agglomeration evolution characteristics of CEE from static and dynamic perspectives by integrating ESDA and Spatial Markov Chains. Then, the spatial heterogeneity of the impacts of multi-dimensional urbanization on CEE were analyzed by using the Geographically and Temporally Weighted Regression (GTWR). The results show that: (1) with the evolution of time, the CEE has a trend of gradual improvement, but the average is 0.4693; (2) from the perspective of spatial static agglomeration, the “hot spots” of CEE mainly concentrated in Shandong Peninsula, Pearl River Delta, and Chengdu-Chongqing urban agglomeration; The dynamic evolution of CEE gradually forms the phenomenon of “club convergence”; (3) urbanization of different dimensions shows spatial heterogeneity to CEE. The impact of economic urbanization in northern cities on CEE shows an inverted “U” shape, and the negative impact of spatial urbanization on CEE appears in the northwest and resource-based cities around Bohai Sea. Population and social urbanization have a positive promoting effect on CEE after 2010. These findings may help China to improve the level of CEE at the city level and provide a reference for low-carbon decision-making.

scholarly journals Impact of Population Aging on Carbon Emission in China: A Panel Data Analysis

2018 ◽  
Vol 10 (7) ◽  
pp. 2458 ◽  
Author(s):  
Weidong Li ◽  
Xin Qi ◽  
Xiaojun Zhao
Keyword(s):  
Panel Data ◽  
Carbon Emission ◽  
Population Aging ◽  
Panel Data Analysis ◽  
Negative Relationship ◽  
Modern Society ◽  
Eastern Region ◽  
Low Carbon ◽  
Stirpat Model ◽  
The Impact

The impact of population structure on carbon emission has always been a key area of research in modern society. In this paper, we propose a new expanded STIRPAT model and panel co-integration method to analyze the relationship between population aging and carbon emission, based on the provincial panel data in China from 1999 to 2014. Empirical results show that there exists a significant inverted U-shaped curve between the population aging and carbon emission. There also exist regional discrepancies, where the impact of the population aging on carbon emission in the eastern region is significantly positive. By contrast, a negative relationship arises in the central and western regions. Finally, several suggestions for low carbon development are provided.

scholarly journals Does Emission Trading Improve Carbon Emission Efficiency of China’s Iron and Steel Industry? An Exploration Using a DEA-SBM and Difference-In-Differences Approach

2021 ◽  
Author(s):  
Xiping Wang ◽  
Sujing Wang
Keyword(s):  
Steel Industry ◽  
Carbon Emission ◽  
Emission Trading ◽  
Energy Structure ◽  
Iron And Steel Industry ◽  
Low Carbon ◽  
Difference In Differences ◽  
Iron And Steel ◽  
Emission Efficiency ◽  
The Impact

Abstract As an effective tool of carbon emission reduction, emission trading has been widely used in many countries. Since 2013, China implemented carbon emission trading in seven provinces and cities, with iron and steel industry included in the first batch of pilot industries. This study attempts to explore the policy effect of emission trading on iron and steel industry in order to provide data and theoretical support for the low-carbon development of iron and steel industry as well as the optimization of carbon market. With panel data of China’s 29 provinces from 2006 to 2017, this study adopted a DEA-SBM model to measure carbon emission efficiency of China’s iron and steel industry (CEI) and a difference-in-differences (DID) method to explore the impact of emission trading on CEI. Moreover, regional heterogeneity and influencing mechanisms were further investigated, respectively. The results indicate that: (1) China's emission trading has a significant and sustained effect on carbon abatement of iron and steel industry, increasing the annual average CEI by 12.6% in pilot provinces. (2) The policy effects are heterogeneous across diverse regions. Higher impacts are found in the western and eastern regions, whereas the central region is not significant. (3) Emission trading improves CEI by stimulating technology innovation, reducing energy intensity, and adjusting energy structure. (4) Economic level and industrial structure are negatively related to CEI, while environmental governance and openness degree have no obvious impacts. Finally, according to the results and conclusions, some specific suggestions are proposed.

scholarly journals The Role of Renewables in a Low-Carbon Society: Evidence from a Multivariate Panel Data Analysis at the EU Level

2019 ◽  
Vol 11 (19) ◽  
pp. 5260 ◽  
Author(s):  
Mihail Busu
Keyword(s):  
Panel Data ◽  
Population Growth ◽  
Co2 Emissions ◽  
Carbon Emission ◽  
Linear Regression Analysis ◽  
Biofuel Production ◽  
Total Carbon ◽  
Low Carbon ◽  
Eu Countries ◽  
The Impact

Low carbon emission has a major positive impact on our society. Due to the importance of reducing carbon emission levels, factors that contribute significantly towards reducing carbon emission levels have attracted the interest of academics and researchers in the field. In this paper, the author develops a multiple linear regression analysis to examine the relationship between renewable energy consumption, biofuel production, resources productivity, bioenergy productivity, the level of urbanization and population and their impact on total carbon dioxide (CO2) emissions. Data was collected from the European Statistical Office (EUROSTAT) and four statistical hypotheses were validated through a regression model with panel data using the statistical software EViews 11. The study was conducted for 27 European Union (EU) countries during 2008 to 2017. The author’s findings indicate that renewables have a direct and positive influence on the levels of CO2 emissions, as opposed to population growth and urbanization. These findings suggest that public policy should be directed towards increasing the use of renewables in EU countries, while the level of urbanization and the population growth add more restrictions in the modelling equation of the impact on CO2 emissions.

scholarly journals Analyzing the Renewable Energy and CO2 Emission Levels Nexus at an EU Level: A Panel Data Regression Approach

Processes ◽  
2021 ◽  
Vol 9 (1) ◽  
pp. 130
Author(s):  
Mihail Busu ◽  
Alexandra Catalina Nedelcu
Keyword(s):  
Renewable Energy ◽  
Panel Data ◽  
Co2 Emissions ◽  
Co2 Emission ◽  
Negative Impact ◽  
National Level ◽  
Renewable Energy Consumption ◽  
Urbanization Level ◽  
Carbon Dioxide Co2 ◽  
The Impact

In the past decades, carbon dioxide (CO2) emissions have become an important issue for many researchers and policy makers. The focus of scientists and experts in the area is mainly on lowering the CO2 emission levels. In this article, panel data is analyzed with an econometric model, to estimate the impact of renewable energy, biofuels, bioenergy efficiency, population, and urbanization level on CO2 emissions in European Union (EU) countries. Our results underline the fact that urbanization level has a negative impact on increasing CO2 emissions, while biofuels, bioenergy production, and renewable energy consumption have positive and direct impacts on reducing CO2 emissions. Moreover, population growth and urbanization level are negatively correlated with CO2 emission levels. The authors’ findings suggest that the public policies at the national level must encourage the consumption of renewable energy and biofuels in the EU, while population and urbanization level should come along with more restrictions on CO2 emissions.

scholarly journals Determinants of Basmati Exports from Pakistan: A Panel Data Analysis

2021 ◽  
Vol 3 (1) ◽  
pp. 12-18
Author(s):  
Muhammad Munwar Hayat ◽  
Raheela Khatoon
Keyword(s):  
Panel Data ◽  
Method Of Moments ◽  
Negative Impact ◽  
Positive Impact ◽  
Panel Data Analysis ◽  
Generalized Method Of Moments ◽  
Trading Partner ◽  
Dummy Variable ◽  
Export Competitiveness ◽  
The Impact

This paper aims to estimate the impact of different factors of basmati exports from Pakistan to its trading partner. Results are obtained by using the Generalized Method of Moments (GMM) model and panel data methodology with a sample of 22 countries for the period of 2003-2019. To estimate the impact of different variables on basmati exports Generalized Method of Moments (GMM) model is used on the panel dataset. The results revealed that the inflation rate of Pakistan has a negative and significant effect on the export competitiveness of Pakistani basmati. The exchange rate of Pakistan has a positive and significant impact on the basmati export, the population of Pakistan has a negative and significant impact on basmati export. Basmati production in Pakistan also has a significant and negative impact on basmati export. The Gross Domestic Product (GDP) of Pakistan has a significant and positive impact on the basmati export while the GDP of the trading partner has a significant and negative impact on the basmati export. The dummy variable for joint border also has a positive and significant impact on basmati exports of Pakistan.

scholarly journals Environmental Regulation for Transfer of Pollution-Intensive Industries: Evidence From Chinese Provinces

2020 ◽  
Vol 8 ◽  
Author(s):  
Weiqing Li ◽  
Huaping Sun ◽  
Yunsu Du ◽  
Ziyao Li ◽  
Farhad Taghizadeh-Hesary
Keyword(s):  
Spatial Heterogeneity ◽  
Environmental Regulation ◽  
Economic Effect ◽  
Clean Energy ◽  
Industrial Sector ◽  
Promoting Effect ◽  
Industrial Transfer ◽  
Theoretical Mechanism ◽  
Threshold Regression Model ◽  
The Impact

How environmental regulations affect the transfer of pollution-intensive industries is the core issue of balanced regional development and pollution reduction in China. This paper analyses the theoretical mechanism of the impact of environmental regulation on industrial transfer based on the distinction between formal environmental regulation and informal environmental regulation. To this aim, the paper selects panel data of 30 provinces in China from 2008 to 2018 and uses the fixed effect econometric model to test the impact of environmental regulation on the transfer of pollution-intensive industries, then uses a threshold regression model to study the threshold characteristics and spatial heterogeneity of environmental regulation on pollution-intensive industrial transfer. The results show a significant inverted U-shaped relationship between formal environmental regulation and the transfer of pollution-intensive industries. The increase of formal environmental regulation intensity affects restraining and then promoting the transfer out of pollution-intensive industries. The promoting effect also shows the characteristics of first increasing and then decreasing, verifying that there are threshold characteristics and spatial heterogeneity. Overall, informal environmental regulation promotes the transfer of pollution-intensive industries and shows the informal regulation’s economic effect. The paper then puts forward the corresponding policy suggestions, including utilizing clean energy-saving technologies in the industrial sector, which is incredibly significant to realize the coordinated development of environmental protection and economy.

scholarly journals Does Water, Waste, and Energy Consumption Influence Firm Performance? Panel Data Evidence from S&P 500 Information Technology Sector

2020 ◽  
Vol 17 (14) ◽  
pp. 5206
Author(s):  
Liliana Nicoleta Simionescu ◽  
Ștefan Cristian Gherghina ◽  
Ziad Sheikha ◽  
Hiba Tawil
Keyword(s):  
Information Technology ◽  
Energy Consumption ◽  
Firm Performance ◽  
Panel Data ◽  
Negative Impact ◽  
Total Energy Consumption ◽  
Technology Sector ◽  
Information Technology Sector ◽  
The Impact ◽  
Water Waste

This paper aimed to investigate the impact of water, waste, and energy consumption on firm performance for a sample of enterprises that belong to the S&P 500 Information Technology sector over the period of 2009–2020. The quantitative framework covered both accounting (e.g., return on assets—ROA; return on common equity—ROE; return on capital—ROC; return on invested capital—ROIC) and market-based measures of performance (e.g., price-to-book value—PB), alongside firm and corporate governance specific variables. By estimating multivariate panel data regression models, the empirical results provided support for a negative impact of total water use on PB but a positive effect on ROA. With reference to the total waste, the econometric outcomes revealed a negative influence on the entire selected performance measures, whereas total energy consumption did not reveal any statistically significant influence.

scholarly journals Optimizing Urban Distribution Routes for Perishable Foods Considering Carbon Emission Reduction

2019 ◽  
Vol 11 (16) ◽  
pp. 4387 ◽  
Author(s):  
Lin ◽  
Zhang ◽  
Wang ◽  
Yang ◽  
Shi ◽  
...  
Keyword(s):  
Carbon Emissions ◽  
Emission Reduction ◽  
Carbon Emission ◽  
Carbon Tax ◽  
Search Algorithm ◽  
Urban Traffic ◽  
Low Carbon ◽  
Carbon Emission Reduction ◽  
Urban Distribution ◽  
The Impact

The increasing demand for urban distribution increases the number of transportation vehicles which intensifies the congestion of urban traffic and leads to a lot of carbon emissions. This paper focuses on carbon emission reduction in urban distribution, taking perishable foods as the object. It carries out optimization analysis of urban distribution routes to explore the impact of low carbon policy on urban distribution routes planning. On the basis of analysis of the cost components and corresponding constraints of urban distribution, two optimization models of urban distribution routes with and without carbon emissions cost are constructed. Fuel quantity related to cost and carbon emissions in the model is calculated based on traffic speed, vehicle fuel quantity and passable time period of distribution. Then an improved algorithm which combines genetic algorithm and tabu search algorithm is designed to solve models. Moreover, an analysis of the influence of carbon tax price is also carried out. It is concluded that in the process of urban distribution based on the actual network information, path optimization considering the low carbon factor can effectively reduce the distribution process of CO2, and reduce the total cost of the enterprise and society, thus achieving greater social benefits at a lower cost. In addition, the government can encourage low-carbon distribution by rationally adjusting the price of carbon tax to achieve a higher social benefit.

Gesetzliche Mitbestimmung und Kapitalrendite Co-Determination and Return on Equity / Co-Determination and Return on Equity

2006 ◽  
Vol 226 (5) ◽  
Author(s):  
Kornelius Kraft ◽  
Marija Ugarkovič
Keyword(s):  
Panel Data ◽  
Capital Market ◽  
Negative Impact ◽  
Supervisory Board ◽  
Limited Liability ◽  
Voting Rights ◽  
Positive Influence ◽  
Return On Equity ◽  
German System ◽  
The Impact

SummaryMany observers regard the German system of codetermination as a very strong intervention into the working of the capital market. With the introduction of the codetermination law in 1976, employee representatives in limited liability companies with more than 2000 employees are entitled to occupy half of the number of seats and are granted nearly 50% of the voting rights on the supervisory board. We investigate the impact of the introduction of the German codetermination law in 1976 which implied an extension of co-determination from third parity to almost parity on return on equity. Our estimations are based on panel data for 179 companies from 1971 to 1976 and from 1981 to 1986, thus allowing for adjustment to the 1976 law. In contrast to frequently raised fears, no negative impact is found. Our empirical results suggest a positive influence from the 1976 strengthening of co-determination law on return on equity.

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