scholarly journals Analysis of Factors Influencing Energy Efficiency Based on Spatial Quantile Autoregression: Evidence from the Panel Data in China

Energies ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 504
Author(s):  
Jinping Zhang ◽  
Qiuru Lu ◽  
Li Guan ◽  
Xiaoying Wang
Keyword(s):  
Energy Efficiency ◽  
Economic Development ◽  
Panel Data ◽  
Industrial Structure ◽  
Mainland China ◽  
Factors Influencing ◽  
Resource Endowment ◽  
Level Of Economic Development ◽  
Quantile Autoregression ◽  
Statistical Yearbook

This research mainly studies the factors influencing the efficiency of energy utilization. Firstly, by calculating Moran’sI and local indicators of spatial association (LISA) of energy efficiency of regions in mainland China, we found that energy efficiency shows obvious spatial autocorrelation and spatial clustering phenomena. Secondly, we established the spatial quantile autoregression (SQAR) model, in which the energy efficiency is the response variable with seven influence factors. The seven factors include industrial structure, resource endowment, level of economic development etc. Based on the provincial panel data (1998–2016) of mainland China (data source: China Statistical Yearbook, Statistical Yearbook of provinces), the findings indicate that level of economic development and industrial structure have a significant role in promoting energy efficient. Resource endowment, government intervention and energy efficiency show a negative correlation. However, the negative effect of government intervention is weakened with the increase of energy efficiency. Lastly, we compare the results of SQAR with that of ordinary spatial autoregression (SAR). The empirical result shows that the SQAR model is superior to SAR model in influencing factors analysis of energy efficiency.

scholarly journals Tax Arrangement and Regional Industrial Restructuring: Evidence from Panel Data in China

2016 ◽  
Vol 2016 ◽  
pp. 1-13
Author(s):  
Jinying Ma ◽  
Xi Zhang ◽  
Feng Tao ◽  
Fuzheng Luo
Keyword(s):  
Economic Development ◽  
Panel Data ◽  
Income Tax ◽  
Industrial Structure ◽  
Econometric Model ◽  
Negative Impact ◽  
Industrial Restructuring ◽  
Development Mode ◽  
Secondary Industry ◽  
Regional Industrial Structure

Regional industrial restructuring has been one of the major items in the transformation of economic development mode. An exploration was made into the influence of tax arrangement on the regional industrial structure by setting up a panel data econometric model based on the evaluation and analysis of the regional industrial structure in China. It was shown that tax arrangement influenced the regional industrial restructuring in terms of three aspects. Microlevel: the turnover tax and income tax appeared with a U-path of influence on upgrading of the industrial structure while appearing with an inverted U-path of influence on rationalization of the industrial structure. In addition, the levy of resource tax had a negative impact on both upgrading and rationalization of the industrial structure. Mesolevel: taxation in the secondary and tertiary industries appeared with a U-path of influence on upgrading of the industrial structure. An increase of taxation in the secondary industry had a negative impact on rationalization of the industrial structure. The taxation in the tertiary industry appeared with an inverted U-path of influence on rationalization of the industrial structure. Macrolevel: the macrotax burden had a U-path of influence on both upgrading and rationalization of the industrial structure.

scholarly journals Do Carbon Emissions and Economic Growth Decouple in China? An Empirical Analysis Based on Provincial Panel Data

Energies ◽  
2019 ◽  
Vol 12 (12) ◽  
pp. 2411 ◽  
Author(s):  
Yu Hao ◽  
Zirui Huang ◽  
Haitao Wu
Keyword(s):  
Economic Growth ◽  
Economic Development ◽  
Panel Data ◽  
Carbon Emissions ◽  
Environmental Kuznets Curve ◽  
Kuznets Curve ◽  
Ekc Hypothesis ◽  
Capita Gross Domestic Product ◽  
Level Of Economic Development ◽  
The Relationship

Global warming has emerged as a serious threat to humans and sustainable development. China is under increasing pressure to curb its carbon emissions as the world’s largest emitter of carbon dioxide. By combining the Tapio decoupling model and the environmental Kuznets curve (EKC) framework, this paper explores the relationship between China’s carbon emissions and economic growth. Based on panel data of 29 provinces from 2007 to 2016, this paper quantitatively estimates the nexus of carbon emissions and economic development for the whole nation and the decoupling status of individual provinces. There is empirical evidence for the conventional EKC hypothesis, showing that the relationship between carbon emissions and per capita gross domestic product (GDP) is an inverted U shape and that the inflection point will not be attained soon. Moreover, following the estimation results of the Tapio decoupling model, there were significant differences between individual provinces in decoupling status. As a result, differentiated and targeted environmental regulations and policies regarding energy consumption and carbon emissions should be reasonably formulated for different provinces and regions based on the corresponding level of economic development and decoupling status.

scholarly journals Evaluation and Influencing Factors of Transportation Industry Energy Efficiency of Changjiang Economic Zone

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Yi Xu ◽  
Xiaojuan Li
Keyword(s):  
Energy Efficiency ◽  
Panel Data ◽  
Data Model ◽  
Evaluation System ◽  
Industrial Structure ◽  
Panel Data Model ◽  
Transportation Industry ◽  
Urgent Task ◽  
Economic Zone ◽  
Opening Up

Changjiang Economic Zone (CEZ) faces the urgent task to promote the energy conservation and emission reduction of the transportation industry. This study constructs an evaluation system for transportation industry energy efficiency (TIEE) and evaluates TIEEs of 11 CEZ provinces in 2000–2017, using the super-slack-based measure (Super-SBM) model containing undesired output. On this basis, the panel data model was adopted to explore the impactors of TIEE. The main results are as follows: CEZ provinces varied significantly in TIEE. In the sample period, Jiangsu, Jiangxi, Zhejiang, Sichuan, Shanghai, and Anhui achieved relatively satisfactory TIEEs; Hunan, Hubei, and Guizhou performed generally on TIEE, calling for some improvement; Chongqing and Yunnan did not perform well, leaving a huge room for improvement. Judging by TIEE trends in the lower reaches, middle reaches, and upper reaches, TIEE of the lower reaches exhibited a U-shaped trend (first decrease and then increase) and TIEEs of the middle reaches and upper reaches did not fluctuate significantly, except for a few years. There was a marked difference between the three regions in TIEE: TIEE in the lower reaches was much higher than that in the middle reaches and upper reaches. In addition, the panel data model demonstrates that TIEE is significantly promoted by economic growth and transportation structure, obviously suppressed by industrial structure, opening-up, and transportation infrastructure, and not clearly affected by government influence or environmental regulation.

scholarly journals Economic Factors Influencing the Level of Economic Development of Multicounty Areas

1972 ◽  
Vol 4 (1) ◽  
pp. 45-51
Author(s):  
Stan Daberkow
Keyword(s):  
Principal Component Analysis ◽  
Economic Development ◽  
Development Process ◽  
Principal Component ◽  
Economic Factors ◽  
Mathematical Identity ◽  
Factor Analyses ◽  
Factors Influencing ◽  
Level Of Economic Development ◽  
Multidimensional Concept

Economic development is an elusive, multidimensional concept. Identification of the interdependencies and interactions underlying the development process seem to call for appropriate multivariate analysis. Principal component and factor analyses were used in a study of socioeconomic interdependencies associated with economic development in multicounty areas in the 48 contiguous States. This paper summarizes some results from that study and explains the use of a mathematical identity relating factor analysis to principal component analysis. This identity explains the level of economic development in terms of alternative levels of factors.

Study on the Non-linear Effect of Tourism Industry Agglomeration on Economic Growth in China——Based on Inter-provincial Panel Data

2021 ◽  
Vol 7 (6) ◽  
pp. 6213-6221
Author(s):  
Lin Li
Keyword(s):  
Economic Growth ◽  
Economic Development ◽  
Panel Data ◽  
Threshold Value ◽  
Tourism Industry ◽  
Linear Effect ◽  
Industry Agglomeration ◽  
Non Linear Effect ◽  
Non Linear ◽  
Level Of Economic Development

Objectives: There are few studies on the non-linear effect of tourism industry agglomeration on economic growth. Based on this, this paper uses the panel data of provinces in 2007-2017 to analyze the spatial characteristics of China's tourism industry agglomeration, and uses the threshold regression model to analyze the role of China's tourism industry agglomeration in promoting economic growth. The results show that: China's tourism industry shows obvious characteristics of spatial agglomeration. The provinces with high degree of industrial agglomeration are mainly Beijing, Shanghai, Yunnan, Guangdong, Guizhou, Sichuan and Shanxi; The non-linear effect of China's tourism industry agglomeration on economic growth is significant. When the level of economic development is less than the threshold value of 10.552, tourism industry agglomeration promotes economic growth. When the level of economic development is greater than the threshold value of 10.552, the impact of tourism industry agglomeration on economic growth is negative. Williamson hypothesis of China's tourism industry agglomeration is established.

scholarly journals Energy Utilization Efficiency of China Considering Carbon Emissions—Based on Provincial Panel Data

2021 ◽  
Vol 13 (2) ◽  
pp. 877
Author(s):  
Ge Huang ◽  
Wei Pan ◽  
Cheng Hu ◽  
Wu-Lin Pan ◽  
Wan-Qiang Dai
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Panel Data ◽  
Industrial Structure ◽  
Negative Impact ◽  
Positive Impact ◽  
Fixed Effect Model ◽  
Energy Utilization ◽  
Utilization Efficiency ◽  
Effect Model

With the development of the economy, environmental pollution caused by energy consumption has become increasingly prominent. Improving the efficiency of energy utilization is an important way to solve this problem. Firstly, we used a data envelopment analysis (DEA) model to calculate the energy utilization efficiency of China’s provinces and regions from the perspective of environmental constraints, including four inputs—labor force, capital stock, energy consumption and carbon emission—and one output, GDP. Secondly, an entity fixed effect model of panel data was built to investigate the influence of openness, urbanization, marketization and industrial structure on energy utilization efficiency in the process of economic structure change. The results indicate that China’s energy efficiency shows a trend of first stabilizing and then declining from 2007 to 2017. Meanwhile, the comprehensive energy efficiency of all provinces and regions is not very ideal. Only Beijing, Shanghai and Guangdong constitute the forefront of China’s energy efficiency. The lack of pure technical efficiency in most provinces is the main reason for the low comprehensive efficiency, but there are also obvious differences among provinces and regions. In addition, urbanization, openness and industrial structure have a negative impact on energy efficiency, while marketization has a significant positive impact on energy efficiency. Finally, based on the regional differences, some suggestions were put forward to improve China’s energy utilization efficiency.

Why Resource-poor Dictators Allow Freer Media: A Theory and Evidence from Panel Data

2009 ◽  
Vol 103 (4) ◽  
pp. 645-668 ◽  
Author(s):  
GEORGY EGOROV ◽  
SERGEI GURIEV ◽  
KONSTANTIN SONIN
Keyword(s):  
Panel Data ◽  
Fixed Effects ◽  
Model Specification ◽  
Size Of Government ◽  
Media Freedom ◽  
Model Free ◽  
Resource Endowment ◽  
Level Of Economic Development ◽  
Free Media ◽  
Rich Countries

Every dictator dislikes free media. Yet, many nondemocratic countries have partially free or almost free media. In this article, we develop a theory of media freedom in dictatorships and provide systematic statistical evidence in support of this theory. In our model, free media allow a dictator to provide incentives to bureaucrats and therefore to improve the quality of government. The importance of this benefit varies with the natural resource endowment. In resource-rich countries, bureaucratic incentives are less important for the dictator; hence, media freedom is less likely to emerge. Using panel data, we show that controlling for country fixed effects, media are less free in oil-rich economies, with the effect especially pronounced in nondemocratic regimes. These results are robust to model specification and the inclusion of various controls, including the level of economic development, democracy, country size, size of government, and others.

scholarly journals Does Financial Development Hamper or Improve the Resource Curse? Analysis Based on the Panel Threshold Effect Model

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
ZhiQiang Sun ◽  
ZeXiang Cai
Keyword(s):  
Economic Development ◽  
Financial Development ◽  
Resource Curse ◽  
Threshold Effect ◽  
Endowment Effect ◽  
Financial Resources ◽  
Threshold Effects ◽  
Effect Model ◽  
Resource Endowment ◽  
Level Of Economic Development

This paper analyzes the “resource curse” and “financial threshold effect” that may exist in China and then uses the data from 30 provinces from 2004 to 2018 as research samples. We used linear regression and nondynamic panel threshold models to analyze the financial threshold effects of the “resource curse” hypothesis and the “resource curse” phenomenon. At the same time, we divided the level of financial development to verify the robustness of the research conclusions in this paper. The study found the following: (1) There is a certain correlation between the abundance of resources and economic growth. Whether this can be seen as a “curse” or a “blessing” of resources is significantly related to the degree of financial development. (2) Whether financial development can alleviate the “resource curse” depends on the degree of financial development. In the extremely scarce stage of financial resources, the resource endowment effect is obvious, and the level of economic development in resource-based regions will be higher than in other regions; when the level of financial development is low (financial resources are not scarce and have not reached a reasonable level), the phenomenon of the “resource curse” appears; when the level of financial development is highly developed, economic development benefits more from financial development, and the effects of resource endowment decline. Only when financial development is at a reasonable level can resource endowments effectively raise the level of economic development.

scholarly journals Analysis of Main Influencing Factors of Global Electrification Development

2020 ◽  
Vol 165 ◽  
pp. 06025
Author(s):  
Junshu Feng ◽  
Peng Wang
Keyword(s):  
Economic Development ◽  
Influencing Factors ◽  
Development Process ◽  
Industrial Structure ◽  
Urbanization Level ◽  
Resource Endowment ◽  
The World ◽  
Development Paths ◽  
Policy Guidance

Based on the analysis of electrification development process in major countries, this paper systematically studied and judged 5 important influencing factors of electrification development in the world, including resource endowment, economic development, improvement of people’s livelihood, infrastructure and policy guidance, among economic development includes industrial structure and urbanization level. The opinions of this paper can support different regions or countries to choose proper electrification development paths.

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