Endogenous Study on Economic Development, Environmental Investment, and Green Development Based on the Panel Data Analysis of 11 Provinces in the Yangtze River Economic Belt

Development is the eternal theme of the times. However, the transformation of the development mode is imminent, and we should abandon the extensive economic development mode and turn to the efficient development of an intensive mode. The high-tech industry will be the decisive force in future industrial development. The agglomeration of the industry will help form economies of scale, thereby improving the effective allocation of resources and promoting productivity. The increase in green economy efficiency is a key factor in achieving green development and an important indicator of achieving the coordinated development of economic development and environmental protection. Therefore, in this study, we try to improve the efficiency of the green economy through industrial agglomeration to achieve green development. In order to solve this problem, we took the Yangtze River Economic Belt as the research object, used Super Slacks-based Measure (SBM) data envelopment analysis (DEA) and general algebraic modeling system (GAMS) to study the green economy efficiency, and then used the system generalized moment method (SGMM) to study the impact of high-tech industry agglomeration on green economy efficiency. According to the empirical test, we found that (1) the green economy efficiency of the Yangtze River Economic Belt shows a volatile upward trend, (2) the green economy efficiency of the Yangtze River Economic Belt differs with time and by region, (3) the agglomeration of the high-tech industry has a lagging effect on the improvement of green economy efficiency, and (4) the regression coefficients of economic development and foreign direct investment are positive and those of environmental regulation and urbanization are negative. Finally, in this paper, we provide corresponding policy recommendations to promote the agglomeration of high-tech industries, thereby improving the efficiency of the green economy.

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Economic Development and Environmental Degradation in Indonesia: Panel Data Analysis

Jurnal Ekonomi & Studi Pembangunan ◽

10.18196/jesp.v22i2.7629 ◽

2021 ◽

Vol 22 (2) ◽

pp. Layouting

Author(s):

M Irsyad Ilham

Keyword(s):

Economic Development ◽

Data Analysis ◽

Panel Data ◽

Population Density ◽

Cross Section ◽

Environmental Degradation ◽

Environmental Quality ◽

Panel Data Analysis ◽

Policy Implications ◽

Environmental Damage

This study analyzed the relationship of economic development, population density, and the number of vehicles on environmental degradation from 31 provinces in Indonesia for the period 2011-2019. Panel data analysis, which is widely used to examine issues that could not be studied in either cross-section or time-series alone, is used herein. The empirical results support the hypothesis on the direction of causality from those three factors of environmental damage in the country. The results concluded that economic development, population density, and the number of vehicles impacted on environmental degradation in Indonesia. The smallest cross-section random effect indicates the lowest environmental quality when all factors are fixed. The empirical findings provide important policy implications for Indonesia and it will direct its economic development model towards a green economic one. On the other hand, the growth of the population should be equalized with growth in human development. The distribution of population should be equalized among provinces by opening a new economic cluster to supply new work-fields. In addition, it should be for the country to create a more-educated population in order to protect environmental quality. Despite the unstoppable growth of vehicles, the government should implement the development of eco-friendly combustion technology besides reducing fuel consumption. Moreover, the road-making by plastic-based material can be considered to prevent land damage from plastic waste and might also recycle plastics which has caused pollution in Indonesia.

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Crime and Economic Development in South Africa: A Panel Data Analysis

International Journal of Economics and Business Administration ◽

10.35808/ijeba/712 ◽

2021 ◽

Vol IX (Issue 2) ◽

pp. 424-438

Author(s):

Leward Jeke ◽

Tafadzwa Chitenderu ◽

Clement Moyo

Keyword(s):

South Africa ◽

Economic Development ◽

Data Analysis ◽

Panel Data ◽

Panel Data Analysis

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Economic Development and Energy Intensity: A Panel Data Analysis

The Econometrics of Energy Systems ◽

10.1057/9780230626317_5 ◽

2007 ◽

pp. 98-120 ◽

Cited By ~ 1

Author(s):

Ghislaine Destais ◽

Julien Fouquau ◽

Christophe Hurlin

Keyword(s):

Economic Development ◽

Data Analysis ◽

Panel Data ◽

Energy Intensity ◽

Panel Data Analysis

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The Relationship Between Sustainable Economic Development and Tourism in Turkey: Panel Data Analysis

Accounting, Finance, Sustainability, Governance & Fraud: Theory and Application - New Approaches to CSR, Sustainability and Accountability, Volume I ◽

10.1007/978-981-32-9588-9_14 ◽

2019 ◽

pp. 249-263

Author(s):

Dilek Tandoğan

Keyword(s):

Economic Development ◽

Data Analysis ◽

Panel Data ◽

Panel Data Analysis ◽

Sustainable Economic Development ◽

The Relationship

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Analysis of China’s Industrial Green Development Efficiency and Driving Factors: Research Based on MGWR

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18083960 ◽

2021 ◽

Vol 18 (8) ◽

pp. 3960

Author(s):

Ke Liu ◽

Yurong Qiao ◽

Qian Zhou

Keyword(s):

Economic Development ◽

Technological Innovation ◽

Yangtze River ◽

Industrial Development ◽

Government Regulation ◽

Industrial Structure ◽

Driving Factors ◽

The Yangtze River ◽

Green Development ◽

The Government

With increasingly severe constraints on resources and the environment, it is the mainstream trend of economic development to reduce industrial pollution emissions and promote green industrial development. In this paper, a super-efficiency slacks-based measure (SBM) model is adopted to measure the industrial green development efficiency (IGDE) of 289 cities in China from 2008 to 2018. Moreover, we analyze their spatiotemporal differentiation pattern. On this basis, the multiscale geographical weighted regression (MGWR) model is used to analyze the scale differences and spatial differences of the driving factors. The results show that the IGDE is still at a low level in China. From 2008 to 2018, the overall polarization of IGDE was relatively serious. The number of high- and low-efficiency cities increased, while that of medium-efficiency cities greatly decreased. Secondly, the IGDE presented an obvious spatial positive correlation. MGWR regression results show that the technological innovation, government regulation, and consumption level belonged to the global scale, and there was almost no spatial heterogeneity. Other driving factors were urbanization, industrial structure, economic development, and population density according to their spatial scale. Lastly, the influence of economic development and technological innovation had a certain circular structure in space; the influence of population size mainly occurred in the cities of the southeast coast and northeast provinces; the influence of urbanization was more obvious in the most northern provinces of the Yangtze River, while that of industrial structure was mainly concentrated in the most southern cities of the Yangtze River Economic Belt (YREB). Spatially, the influence of consumption was manifested as a distribution trend of decreasing from north to south, and the government regulation was manifested as increasing from west to east and then to northeast.

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