scholarly journals Characterizing the Influences of Economic Development, Energy Consumption, Urbanization, Industrialization, and Vehicles Amount on PM2.5 Concentrations of China

2018 ◽  
Vol 10 (7) ◽  
pp. 2574 ◽  
Author(s):  
Haoran Zhao ◽  
Sen Guo ◽  
Huiru Zhao
Keyword(s):  
Economic Development ◽  
Energy Consumption ◽  
Industrial Development ◽  
Driving Forces ◽  
Gdp Per Capita ◽  
Kuznets Curve ◽  
Urbanization Process ◽  
Distributed Lag ◽  
Real Gdp Per Capita ◽  
Per Capita

The speeding-up of economic development and industrialization processes in China have brought about serious atmospheric pollution issues, especially in terms of particulate matter harmful to health. However, impact mechanisms of socio-economic forces on PM2.5 (the particle matter with diameter less than 2.5 μm) have rarely been further investigated. This paper selected GDP (gross domestic product) per capita, energy consumption, urbanization process, industrialization structure, and the amount of possession of civil vehicles as the significant factors, and researched the relationship between these factors and PM2.5 concentrations from 1998 to 2016, employing auto-regressive distributed lag (ARDL) methodology and environmental Kuznets curve (EKC) theory. Empirical results illustrated that a long-term equilibrium nexus exists among these variables. Granger causality results indicate that bi-directional causality exist between PM2.5 concentrations and GDP per capita, the squared component of GDP per capita, energy consumption and urbanization process. An inverse U-shape nexus exists between PM2.5 concentrations and GDP per capita. When the real GDP per capita reaches 5942.44 dollars, PM2.5 concentrations achieve the peak. Results indicate that Chinese governments should explore a novel pathway to resolve the close relationship between socio-economic factors and PM2.5, such as accelerating the adjustment of economic development mode, converting the critical industrial development driving forces, and adjusting the economic structure.

Energy consumption flow and regional economic development: evidence from 25 economies

2017 ◽  
Vol 12 (1) ◽  
pp. 96-118 ◽  
Author(s):  
Bao-jun Tang ◽  
Pi-qin Gong ◽  
Yu-chong Xiao ◽  
Huai-yu Wang
Keyword(s):  
Cluster Analysis ◽  
Economic Development ◽  
Energy Consumption ◽  
Negative Relationship ◽  
Regional Economic Development ◽  
Embodied Energy ◽  
Gdp Per Capita ◽  
Regional Economic ◽  
Content Type ◽  
Per Capita

Purpose This paper aims to figure out the relationship between energy consumption flow from a new perspective of embodied energy inventory index (EEII) and regional economic growth. Design/methodology/approach The input-output approach has been applied to calculate embodied energy inventory (EEI) and EEII using the data of 25 economies. Meanwhile, cluster analysis and panel data modeling were applied to carry out detailed research. Findings The results of cluster analysis show that there is a roughly negative relationship between EEII and gross domestic product (GDP) per capita, although there are some exceptions, such as Russia and Taiwan (Province of China). Panel data model results provide further evidence that there is a negative relationship between EEII and GDP per capita. Population is an important productive factor in the regional economic development. The study showed a positive relationship between EEII and population. Therefore, energy consumption flow is closely related to regional economic development. Originality/value The value of this paper is to use EEI and EEII to comprehensively clarify the energy consumption flow. The advantage of EEII is that it can reflect the energy embodied in fixed assets and infrastructure.

Energy consumption and economic development in Guangdong, China: Distribution, relationship and causes

2021 ◽  
Author(s):  
Mengmeng Hu ◽  
Yafei Wang ◽  
Beicheng Xia ◽  
Guohe Huang
Keyword(s):  
Economic Growth ◽  
Economic Development ◽  
Energy Consumption ◽  
Energy Intensity ◽  
Hot Spot ◽  
Generalized Method Of Moments ◽  
Gdp Per Capita ◽  
Per Capita ◽  
The Pearl River ◽  
Panel Vector Autoregression

Abstract Analysing the relationship between energy consumption and economic growth is essential to achieve the goal of sustainable development. We employ hot spot analysis to discover the spatial agglomeration of GDP per capita and energy intensity in Guangdong, China, from 2005–2018. Furthermore, panel vector autoregression coupled with a system generalized method of moments is performed to examine the dynamic causal relationship between energy consumption and economic growth under the framework of the Cobb-Douglas production function. Using a multivariate model and grouped studies based on the differences in regional economic development, we show that the GDP per capita of the Pearl River Delta (PRD) is significantly higher than that of the peripheral municipalities. However, energy intensity shows an entirely different spatial distribution. The development of the regional economy depends on its own “assembling effect”. GDP explains approximately 68.3% of the total variation in energy consumption in the PRD and only approximately 34.5% of that in the peripheral municipalities. We do not confirm Granger causality between energy consumption and economic development. Guangdong can decrease its energy consumption growth without substantially sacrificing its economic growth. The analysis framework of this paper has significant implications for regions in balancing economic development and energy consumption.

scholarly journals MARRIAGE AND ECONOMIC DEVELOPMENT IN THE TWENTIETH CENTURY

2017 ◽  
Vol 83 (4) ◽  
pp. 379-420
Author(s):  
Alessio Moro ◽  
Solmaz Moslehi ◽  
Satoshi Tanaka
Keyword(s):  
Economic Development ◽  
Family Formation ◽  
Value Added ◽  
Gdp Per Capita ◽  
Extensive Literature ◽  
Data Set ◽  
Real Gdp ◽  
Real Gdp Per Capita ◽  
Per Capita ◽  
Cross Country

Abstract:There is an extensive literature discussing how individuals’ marriage behavior changes as a country develops. However, no existing data set allows an explicit investigation of the relationship between marriage and economic development. In this paper, we construct new cross-country panel data on marital statistics for 16 OECD countries from 1900 to 2000, in order to analyze such a relationship. We use this data set, together with cross-country data on real GDP per capita and the value added share of agriculture, manufacturing, and services sectors, to document two novel stylized facts. First, the fraction of a country’s population that is married displays a hump-shaped relationship with the level of real GDP per capita. Second, the fraction of the married correlates positively with the share of manufacturing in GDP. We conclude that the stage of economic development of a country is a key factor that affects individuals’ family formation decisions.

Energy Consumption - Economic Growth Relationship and Carbon Emissions in Twelve Provinces of West of China

2012 ◽  
Vol 178-181 ◽  
pp. 885-892 ◽  
Author(s):  
Yong Ping Bai ◽  
Jing Yang
Keyword(s):  
Economic Growth ◽  
Energy Consumption ◽  
Carbon Emissions ◽  
Income Elasticity ◽  
Gdp Per Capita ◽  
Great Effort ◽  
Real Gdp ◽  
Real Gdp Per Capita ◽  
Per Capita ◽  
Level Group

This paper applies the panel unit root, heterogeneous panel cointegration and panel-based dynamic OLS to re-investigate the co-movement and relationship between energy consumption and economic growth for 12 provinces(autonomous regions, municipalities) in West of China from 1989 to 2009. The empirical results show that there is a positive long-run cointegrated relationship between real GDP per capita and energy consumption variables. Furthermore, we investigate three cross-regional groups, namely the stronger-level, medium-level and weaker-level groups, and get more important results and implications. In the long-term, a 1% increase in real GDP per capita increases the consumption of energy by different rates for three groups respectively, and subsequently it increases at different rates in three groups of the carbon emissions in West of China. The economic growth in stronger-level group is energy-dependent to a great extent, and the income elasticity of energy consumption in stronger-level group is over several times than that of the weaker-level groups. At present, West of China are subject to tremendous pressures formitigating climate change issues. It is possible that the GDP per capita elasticity of carbon emissions would be controlled in a range that orients sustainable development by the great effort.

scholarly journals The Impact of CO2 Emissions on the GDP per Capita, Employment Rate and Energy Consumption of China, Korea and Japan

2021 ◽  
Vol 6 (11) ◽  
pp. 315-333
Author(s):  
Allieah A. Mendoza ◽  
Kirby Duane Garret T. Reyes ◽  
Pauline Antonette D. Soriano ◽  
Ronaldo Cabauatan
Keyword(s):  
Energy Consumption ◽  
Co2 Emissions ◽  
Time Series Data ◽  
Gdp Per Capita ◽  
Series Data ◽  
Kuznets Curve ◽  
Total Employment ◽  
Cointegration Tests ◽  
Per Capita ◽  
The Impact

This paper aims to investigate the relationship between CO2 Emissions and GDP per capita of three East Asian countries (China, Japan, and South Korea). The Environmental Kuznets Curve hypothesis and its possible implications to the implementation of the Kyoto Protocol Agreement will be tested. The independent variables Employment and Energy consumption will be used as control variables. Multiple regression analysis and cointegration tests will be used on time series data of Japan, Korea, and China that is obtained from the World Bank database. GDP per capita is measured in constant 2010 US$, CO2 emission in kt, Employment in the ratio of total employment to total population aged 15 and above, and Energy Consumption in annual kWh per capita.

scholarly journals Trends and Driving Forces of Carbon Emissions from Energy Consumption: A Case Study of Nanjing, China

2018 ◽  
Vol 10 (12) ◽  
pp. 4348 ◽  
Author(s):  
Kong-Qing Li ◽  
Ran Lu ◽  
Rui-Wen Chu ◽  
Dou-Dou Ma ◽  
Li-Qun Zhu
Keyword(s):  
Growth Rate ◽  
Energy Consumption ◽  
Carbon Emissions ◽  
Driving Forces ◽  
Positive Impact ◽  
High Growth ◽  
Future Trend ◽  
Gdp Per Capita ◽  
Stirpat Model ◽  
Per Capita

Based on the scientific calculation of carbon emissions from energy consumption in Nanjing, this paper analyzed the driving forces of carbon emissions from 2000 to 2016 by using the stochastic impacts by regression on population, affluence and technology (STIRPAT) model. The results show that from 2000 to 2016, the energy carbon emissions of Nanjing were on the rise; the urbanization rate, population, GDP per capita, and energy intensity had a significant positive impact on the growth of carbon emissions in Nanjing, China. Based on this, we presented five development scenarios to analyze the future trend of carbon emissions of the city. By contrast, the growth rate of carbon emissions from energy consumption is the slowest when the population maintains a low growth rate and the GDP per capita and technical level maintain high growth. This indicates a better urban development strategy in which industrial restructuring must be associated with talent structure adjustment to decarbonize the urban economy, and the extensive urban sprawl development approach might need to be changed.

scholarly journals Causality relationship between economic growth and environmental degradation. Case G-8

2021 ◽  
Vol 25 (111) ◽  
pp. 165-173
Author(s):  
Victor Quinde Rosales ◽  
Rina Bucaram Leverone ◽  
Martha Bueno Quinonez ◽  
Michelle Saldana Vargas
Keyword(s):  
Economic Growth ◽  
New York ◽  
Economic Development ◽  
Carbon Emissions ◽  
Environmental Kuznets Curve ◽  
Quarterly Journal ◽  
Gdp Per Capita ◽  
Kuznets Curve ◽  
Per Capita ◽  
Environment And Development

This article is an inductive argumentation and an empirical-analytical paradigm that evaluates the actual relationship between Gross Domestic Product (GDP) per capita and the Carbon Dioxide (CO2) in country groups of the G8 considered as developed in a period of time from 1960 to 2011. It was developed an Augmented Dickey-Fuller unit root (ADF), a Granger Causality Test and a Johansen Cointegration test. The results evidence the non-stationary of constrains in both countries. It was obtained a VAR model with two variables with a number of lags of four - VAR2 (4) to which were tested for causality by demonstrating a unidirectionality of GDP per capita to CO2. Keywords: economic growth, economic development, income distribution, environmental economics. References [1]G. Brundtland, «Our Common Future,» de Report of the World Commission on Environment and Development , 1987. [2]R. Bermejo, Del desarrollo sostenible según Brundtland a la sostenibilidad como biomimesis, Bilbao: Hegoa, 2014. [3]R. B. and. P. C. Fander Falconí, «Flacso,» 16 03 2016. [Online]. Available: https://www.flacsoandes.edu.ec/agora/62767-la-discutible-curva-de-kuznets. [Last access: 15 01 2021]. [4]E. Urteaga, «Las teorías económicas del desarrollo sostenible,» Cuadernos de Economía, vol. 32, nº 89, pp. 113-162, 2009. [5]V. K. Smith, Scarcity and Growth Reconsidered, Baltimore: The Johns Hopkins Press, 1979. [6]J. y. A. Medina, «Ingreso y desigualdad: la Hipótesis de Kuznets en el caso boliviano,» Espacios, vol. 38, nº31, p. 23, 2017. [7]M. Ahluwalia, «Inequality, poverty and development, » Journal of Development Economics, nº 3, pp. 307-342, 1976. [8]A. and R. D. Alesina, «Distributive politics and economic growth,» Quarterly Journal of Economics, vol. 109, nº 2, pp. 465-490, 1994. [9]R. Barro, «Inequality and growth in a panel of countries, » Journal of Economic Growth, vol. 5, nº 1, pp. 5-32, 2000. [10]M. A. Galindo, «Distribución de la renta y crecimiento económico,» de Anuario jurídico y económico escurialense, 2002, pp. 473-502. [11]A. Álvarez, «Distribución de la renta y crecimiento económico, Información Comercial Española, ICE,» Revista de economía, nº 835, pp. 95-100, 2007. [12]J. C. Núñez, «Crecimiento económico y distribución del ingreso: una perspectiva del Paraguay,» Población y Desarrollo, nº 43, pp. 54-61, 2016. [13]S. Kuznets, «Economic Growth and Income Inequality, » American Economic Review, nº 45, pp. 1-28, 1955. [14]J. A. and. C. J. Araujo, «Relación entre la desigualdad de la renta y el crecimiento económico en Brasil: 1995-2012.,» Problemas del desarrollo, vol. 46, nº 180, pp.129-150, 2015. [15]F. V. A. and P. C. Correa, «La Curva Medioambiental de Kuznets: Evidencia Empírica para Colombia Grupo de Economía Ambiental (GEA),» Semestre Económico, vol. 8, nº 15, pp. 13-30, 2005. [16]W. Malenbaum, World Demand for Raw Materials in 1985 and 2000, McGraw-Hill: New York, 1978. [17]W. Beckerman, «Economists, scientists, and environmental catastrophe,» Oxford Economic Papers, vol. 24, nº 3, 1972. [18]G. y. K. A. Grossman, «Economic Growth and the Environment,» The Quarterly Journal of Economics, vol. 110, nº 2, pp. 353-377, 1995. [19]N. Stokey, «Are there Limits to Growth?,» International Economic Review, vol. 39, nº 1, 1998. [20]W. and. C. W. Jaeger, «A Theoretical Basis for the Environmental Inverted-U Curve and Implications for International Trade,» de Discussant: Clive Chapple, New York, 1998. [21]T. B. K. B. R. and. G. K. Cavlovic, «A Mets-Analysis of Environmental Kuznets Curve Studies,» Agricultural and Resource Economics, nº 29, pp. 32-42, 2000. [22]M. and. S. T. Heil, «Carbon emissions and economic development: future trajectories based on historical experience, » Environment and Development Economics, vol. 6, nº 1, pp. 63-83, 2001. [23]U. S. R. and E. B. Soytas, «Energy consumption, income, and carbon emissions in the United States,» Ecological Economics, vol. 62, nº 3, pp. 482-489, 2007.[24]C. W. J. Granger, «Investigating causal relations by econometrics models and cross spectral methods,» Econometrica, nº 37, pp. 424-438, 1969. [25]M. and U. R. Nasir, «Environmental Kuznets Curve for carbon emissions in Pakistan: An empirical investigation,» Energy Policy, vol. 39, nº 3, pp. 1857-1864,2011. [26]S. Johansen, «Statistical Analysis of Cointegration Vectors,» Journal of Economic Dynamics and Control, vol. 12, nº 2, pp. 231-254, 1988. [27]B. Goldman, «Meta-Analysis of Environmental Kuznets Curve Studies: Determining the Cause of the Curve’s Presence,» de Honors Projects, 2012. [28] M. B.  and T. T. Fosten, «Dynamic misspecification in the environmental Kuznets curve: Evidence from CO2 and SO2 emissions in the United Kingdom,» Ecological Economics, vol. 76, pp. 25-33, 2012.  

scholarly journals Road Safety and Economic Development in Cameroon: An Analysis of the Kuznets Curve

2020 ◽  
Vol 8 (07) ◽  
pp. 1876-1882
Author(s):  
Nodem Meli Clement ◽  
Marie Louise Simone Nyonkwe Ngo Ndjem ◽  
Douanla Meli Steve
Keyword(s):  
Economic Development ◽  
Road Safety ◽  
Inflection Point ◽  
Negative Impact ◽  
Living Conditions ◽  
Gdp Per Capita ◽  
Kuznets Curve ◽  
Road Accidents ◽  
Level Of Economic Development ◽  
Per Capita

This article analyses the situation of road safety in Cameroon and its relationship with the country's level of economic development. The approach of Kuznets (1955) is applied to road accidents in Cameroon over a period from 1977 to 2016. The article identifies a Kuznets relationship for road accidents. The results of the analysis show that there is an inverted U-shaped relationship between road accidents and GDP per capita in Cameroon. The results of the analysis show that there is an inverted U-shaped relationship between road accidents and GDP per capita in Cameroon. Precisely the improvement of living conditions has first of all a negative impact on road safety up to a certain point called the inflection point which corresponds to a growth rate of GDP per capita between 7 and 8%, from this point on the improvement of living conditions positively influences road safety. Keywords: road insecurity, economic development, Kuznets curve, economic development, Cameroon

Development Trajectories in Africa

2019 ◽  
Author(s):  
Richard E. Mshomba
Keyword(s):  
Economic Development ◽  
Growth Rates ◽  
Sub Saharan Africa ◽  
Gdp Per Capita ◽  
African Countries ◽  
Annual Average ◽  
Real Gdp ◽  
Real Gdp Per Capita ◽  
Per Capita ◽  
Sub Saharan

Since independence, African states have been striving for economic development, but relatively few countries have achieved their goal. Between 1970 and 2016, real GDP per capita in sub-Saharan Africa grew by an annual average of just 0.48%. However, there was a wide range of economic performance across different countries, as well as clear variation in growth rates over time. Countries such as the Central African Republic, Democratic Republic of Congo, Liberia, and Madagascar had, on average, a negative growth rate in terms of real GDP per capita. Meanwhile, countries such as Botswana, Lesotho, Mauritius, Seychelles, and Swaziland had positive average annual growth rates of at least 3%. The differences in economic growth rates reflect the diversity of economic structures, governance, and political stability across African states. Although deeper economic integration among African countries may work to reduce the large disparities in economic development, any projections must nonetheless recognize that countries will differ in their economic trajectories. Variation over time is also important. The dominant patterns of economic development in sub-Saharan Africa in the 1980s and 1990s on the one hand, and the 1970s and past the 1990s on the other, were quite different, reflecting a long business cycle. If we look solely at economic growth statistics, the 1980s and 1990s can be described as lost decades. On average, real GDP per capita on the continent declined annually by 1.54% and 0.62% in the 1980s and 1990s, respectively. By contrast, between 2000 and 2016, real GDP per capita increased by an annual average of 2.13%. One important debate has focused on whether these shifts are primarily the result of domestic or international factors. Structural adjustment programs (SAPs) imposed by the International Monetary Fund (IMF) and the World Bank have been blamed for the decline in the economic fortunes of African countries in the 1980s. At the same time, they are praised for pulling many countries out of unsustainable macroeconomic policies. Moreover, a balanced overview of Africa’s development trajectory must conclude that even without major policy shifts such as those brought forth by the SAPs, many countries would still have remained highly dependent on one or just a few commodities, and would therefore have continued to experience wild swings in their business cycles in the absence of international intervention. The lack of economic diversification of many economies on the continent means that the future is hard to predict. However, the prerequisites for a prosperous Africa are not a mystery—they include good governance, economic diversity, and genuine economic integration.

scholarly journals Relationship among Energy Consumption, Inflation, Human Capital and Economic Growth: Evidence from Indonesia

2020 ◽  
Vol 6 (2) ◽  
pp. 85
Author(s):  
Mohammed Hadi ◽  
George Campbell
Keyword(s):  
Economic Growth ◽  
Human Capital ◽  
Energy Consumption ◽  
Unit Root Test ◽  
Secondary Data ◽  
Time Frame ◽  
Gdp Per Capita ◽  
Distributed Lag ◽  
Per Capita ◽  
Human Capital Index

The main focus of the study was to evaluate the relationship among energy consumption, human capital, inflation and economic growth in the case of Indonesia. The study uses secondary data to conduct the study on Indonesia. The rationale behind selecting the secondary data collection method is to draw the analysis and results on the basis of existing information rather than relying over human perspective of opinions. The data in the study consist of energy consumption, human capital index, GDP per capita and inflation. The time frame that is selected for the collection of data is from 1970 till 2018 which overall makes the time period of 49. The tools that are adopted for conducting the analysis is the unit root test and autoregressive distributed lag (ARDL). The result of the study has revealed that the human capital has a significant influence on the energy consumption of Indonesia. The other elements that are also found to have significant impact are the lag of energy consumption, GDP per capita and lag of GDP per capita. With the higher consumption of energy along with the increasing human capital is significantly and positively influencing the GDP growth of Indonesia.

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