Journal articles: 'GDP ENERGY INTENSITY'

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Bennouna, Amin, and Charaf El Hebil. "Energy needs for Morocco 2030, as obtained from GDP-energy and GDP-energy intensity correlations." Energy Policy 88 (January 2016): 45–55. http://dx.doi.org/10.1016/j.enpol.2015.10.003.

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Ang, B. W., and Tian Goh. "Bridging the gap between energy-to-GDP ratio and composite energy intensity index." Energy Policy 119 (August 2018): 105–12. http://dx.doi.org/10.1016/j.enpol.2018.04.038.

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Desai, Dinesh. "Energy-GDP relationship and capital intensity in LDCs." Energy Economics 8, no. 2 (April 1986): 113–17. http://dx.doi.org/10.1016/0140-9883(86)90035-6.

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Prokopyev, Mikhail G. "Targets and the problem of their implementation in the field of energy saving: reducing the energy intensity of GDP." Market economy problems, no. 3 (2020): 21–30. http://dx.doi.org/10.33051/2500-2325-2020-3-21-30.

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The article considers the problem of increasing the energy efficiency of the economy, in particular, reducing the energy intensity of GDP. The basic factors determining the dynamics of energy intensity of GDP are analyzed. Possible scenarios of changes in the energy intensity of GDP depending on the level of GDP and domestic primary energy consumption are presented. The problem of achieving the set goals is considered. It is shown that the unattainability of the target (desired) level of energy intensity of GDP in the declared (designated) terms with the specific impact of instruments of a particular economic policy is the result of many factors. It is concluded that the set goals in energy saving were not achieved in the planned time frame, and the possibility of their implementation in the current trends of economic development (even taking into account their revision in the medium term) is not obvious. To reduce the energy intensity of GDP, it is necessary in practice to implement a decoupling strategy: to ensure economic growth without an increase in the use of resources due to their more rational use and application of the best available technologies.

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A., Bernard O., Adenuga Oludare, and K. U. Nnadi. "Measruring Energy Efficiency in Nigeria : Energy Intensity and Energy-GDP Elasticity Approach." Singaporean Journal of Business Economics and Management Studies 5, no. 5 (August 2016): 29–37. http://dx.doi.org/10.12816/0033267.

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Hannesson, Rögnvaldur. "CO2 intensity and GDP per capita." International Journal of Energy Sector Management 14, no. 2 (November 1, 2019): 372–88. http://dx.doi.org/10.1108/ijesm-02-2019-0011.

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Purpose To investigate whether CO2 intensity falls at a diminishing rate as countries grow richer. Design/methodology/approach Regression of CO2 intensity on the gross domestic product (GDP) per capita, including squared and cubic terms, for a panel of countries and individual countries. Findings CO2 intensity falls at a diminishing rate as countries grow richer. Originality/value Many studies have found that CO2 intensity falls with GDP per capita, but whether it does so at a diminishing rate has not been investigated. This result suggests that structural changes in GDP (more services) as countries get richer will provide little or no help toward decarbonization. It is shown that the extraction of minerals critical for industrial production has increased on par with real GDP. This could explain why CO2 emissions fall at a diminishing rate.

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., Akbar Ullah, Karim Khan, and Munazza Akhtar. "Energy Intensity: A Decomposition Exercise for Pakistan." Pakistan Development Review 53, no. 4II (December 1, 2014): 531–49. http://dx.doi.org/10.30541/v53i4iipp.531-549.

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Since the recent energy crises, the research in this strand has increased considerably. A variety of its dimensions have been examined in the literature. For instance, higher energy prices; instability in the supplies of its various components; its rapid depletion and global warming are some of its dimensions, which have been the focus of discourse among both researchers and policy-makers. Equally, energy intensity measuring the energy consumption to GDP ratio has been an important component of energy policies [Ang (2004); Liu and Ang (2007); Jimenez and Mercado (2013)]. In particular, there is a special focus on sorting out the contribution of energy efficiency— ratio of sectoral specific energy consumption to sectoral GDP—to alienate the impact of efficiency on energy intensity from other relevant factors. This is because energy efficiency is recognised as one of the most cost-effective strategies to address crosscutting issues of energy security, climate change and competitiveness [IDB (2012)]. Consequently, the information regarding energy intensity, its efficiency or activity aspects are useful tools for policy decisions and evaluation and are regularly in practice in most of the advanced countries

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Li, Xiang Qian. "District Energy-Saving Measures and their Selection Method." Advanced Materials Research 724-725 (August 2013): 951–54. http://dx.doi.org/10.4028/www.scientific.net/amr.724-725.951.

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Per GDP energy consumption is the main indicator of district energy-saving effect. The Article firstly analyzed the influence factors of per GDP energy consumption. Then summarized energy-saving measures as six aspects: optimizing industrial structure; reducing energy intensity of industries; reducing per capita household energy consumption; limiting resident population; improving efficiency of energy conversion; improving energy storage and transportation management level. According to implementing body, energy-saving measures are divided into government measure and enterprise measure. District energy-saving measures mainly refer to the government measures. The selection course of district energy-saving measures is divided into five steps: initial prediction of per GDP energy consumption of term-end; analysis of measures of reducing industry energy intensity, per capita household energy consumption and energy loss; second prediction of per GDP energy consumption of term-end; compare with the target value; determination of district energy-saving measures.

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Babets, I. "PROVIDING ENERGY SECURITY OF UKRAINE IN CONDITIONS OF GEOPOLITICAL TRANSFORMATIONS." ACTUAL PROBLEMS OF INTERNATIONAL RELATIONS, no. 132 (2017): 125–37. http://dx.doi.org/10.17721/apmv.2017.132.0.125-137.

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In the article the major trends in the energy sector of Ukraine in modern geopolitical conditions are investigated. The status and dynamics of energy security of Ukraine during 2007–2015 years are evaluated. The main factors strengthening the energy security of Ukraine in 2015 – the decrease of energy intensity of GDP and improving of the diversification of supply sources and kinds of energy resources are detected. The impact of key threats caused by geopolitical changes on the level of energy security of Ukraine is determined. The probability and preconditions of implementation of optimistic, basic, pessimistic scenarios of changes in such key factors of energy security, as energy intensity of GDP and the share of the dominant fuel in total energy consumption are substantiated. Directions of strengthening the energy security of Ukraine in terms of geopolitical transformations, comprehensive reforms of the production and import of energy production, distribution and the use of electricity; further reducing of energy intensity of GDP through economic restructuring and increasing the share of services and high-tech industries in GDP, energy efficiency enterprises of old industrial areas and their technical modernization.

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Song, Yu Chen, Jin Ke Liu, and Hai Dong Meng. "Study on Economic Development of Inner Mongolia Based on Energy." Advanced Materials Research 524-527 (May 2012): 2926–30. http://dx.doi.org/10.4028/www.scientific.net/amr.524-527.2926.

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This paper applies ARIMA model to predict total energy consumption and GDP in 2011-2015, and then reach a conclusion that both are showing a sharp rise trend. Through the analysis on energy intensity in 2001-2015 and energy elasticity between China and Inner Mongolia in 2001-2009, we draw a conclusion that GDP mainly depends on energy consumption and the speed of it increases more than that of GDP in Inner Mongolia. Based on above empirical analysis, we give the corresponding conclusion and suggestion for economic development as follows: prevent the rapid economic growth from high energy consumption; develop the tertiary industry and control economy growth in high energy intensity; change the structure of investment and strengthen the awareness of energy saving and environmental protection.

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Ben Mbarek, Mounir, Nadia Ben Ali, and Rochdi Feki. "Causality relationship between CO2 emissions, GDP and energy intensity in Tunisia." Environment, Development and Sustainability 16, no. 6 (March 18, 2014): 1253–62. http://dx.doi.org/10.1007/s10668-014-9525-x.

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Meng, Zhaosu, Huan Wang, and Baona Wang. "Empirical Analysis of Carbon Emission Accounting and Influencing Factors of Energy Consumption in China." International Journal of Environmental Research and Public Health 15, no. 11 (November 5, 2018): 2467. http://dx.doi.org/10.3390/ijerph15112467.

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China is confronting great pressure to reduce carbon emissions. This study focuses on the driving factors of carbon emissions in China using the Logarithmic Mean Divisia Index (LMDI) method. Seven economic factors, including gross domestic product (GDP), investment intensity, research and development (R&D) intensity, energy intensity, research and development (R&D) efficiency, energy structure and province structure are selected and the decomposition model of influencing factors of carbon emissions in China is constructed from a sectoral perspective. The influence of various economic factors on carbon emissions is analyzed quantitatively. Results show that the R&D intensity and energy intensity are the main factors inhibiting the growth of carbon emissions. GDP and investment intensity are the major factors promoting the growth of carbon emissions. The contribution of R&D efficiency to carbon emissions is decreasing. The impacts of energy structure and province structure on carbon emissions are ambiguous through time. Finally, some policy suggestions for strengthening the management of carbon emissions and carbon emission reduction are proposed.

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Kuzovkin, A. I. "Forecast for GDP energy intensity in 2020: Russia and other developed countries." Studies on Russian Economic Development 21, no. 3 (May 2010): 328–31. http://dx.doi.org/10.1134/s1075700710030111.

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Sun, J. W. "Energy intensity versus per capita GDP in seven developing countries, 1973-1995." International Journal of Global Energy Issues 20, no. 1 (2003): 95. http://dx.doi.org/10.1504/ijgei.2003.003599.

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Wang, Ping, Wan Shui Wu, and Bang Zhu Zhu. "Using LMDI Method to Analyze the Energy-Related CO₂ Emissions in Guangdong Province, China." Applied Mechanics and Materials 291-294 (February 2013): 1556–61. http://dx.doi.org/10.4028/www.scientific.net/amm.291-294.1556.

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In recent years, Guangdong has achieved remarkable performance in economic development; meanwhile it is being faced with problems of increasing CO2 emissions. Following the IPCC Guidelines for National Greenhouse Gas Inventories, we estimated the energy-related CO2 emissions in Guangdong during the period of 1980-2010. We employed the logarithmic mean divisia index (LMDI) method to decompose the CO2 emissions into energy intensity, energy structure, per capita GDP and population scale effects. Besides, we deduced the calculation methods for the year by year effects, the accumulated effects and the contribution degrees. Using 1980 as the base year, the empirical results show that the accumulated effects of energy intensity and energy structure in 2010 are negative, while those of per capita GDP and population scale are positive. Per capita GDP is the chief positive influence on the CO2 emissions. Energy intensity is becoming more significant; however, its direction is instability. Population scale has a significant positive effect on the CO2 emissions. Energy structure has a negligible negative impact on the CO2 emissions. Some suggestions on CO2 emissions reduction in Guangdong are given based on the analysis.

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Lv, Tianxiang, and Xu Wu. "Using Panel Data to Evaluate the Factors Affecting Transport Energy Consumption in China’s Three Regions." International Journal of Environmental Research and Public Health 16, no. 4 (February 14, 2019): 555. http://dx.doi.org/10.3390/ijerph16040555.

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In China, transportation accounts for a large proportion of total energy consumption and that trend is projected to increase in the future. Through the stochastic impacts by regression on population, affluence, and technology (STIRPAT) model, OLS regressions were conducted to investigate the impacts of gross domestic product (GDP), urbanization, energy intensity and transport structure on the transport energy consumption in China’s three regions. The analyses of inter-provincial panel data during the period 2006–2015 is compared to the analysis of the data from 1996 to 2005 to determine the change. There were two primary findings from this study. First, the changes of the influencing degree in three regions are considered. GDP is still the main driver of transport energy consumption in eastern region, while urbanization becomes the main driver in the other two regions. Second, the relationship between the elasticity and the value of each variable is detected. The elasticity of transport energy consumption with respect to GDP, transport structure, energy intensity and urbanization have separate positive and significant relationships. The primary measure is to optimize transport structure in the central region, while reducing energy intensity in the western region. Finally, we propose relevant policy recommendations for the three regions.

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Illarionov, A., and N. Pivovarova. "Economic Consequences of Ratification of the Kyoto Protocol by the Russian Federation." Voprosy Ekonomiki, no. 11 (November 20, 2004): 34–59. http://dx.doi.org/10.32609/0042-8736-2004-11-34-59.

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Carbon dioxide emissions are the inevitable result of hydrocarbon consumption, that is the energy pillar of the modern civilization. These emissions are the function of economic activity and carbon intensity of GDP. With strict natural limits on speed of reduction in the carbon intensity of GDP restraining CO2 emissions means restraining energy consumption and economic activity. Ratification of the Kyoto Protocol by the Russian Federation means that for the first time in the Russian history legal binding limits are put on absolute size of the Russian economy.

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Honningdal Grytten, Ola, Magnus Lindmark, and Kjell Bjørn Minde. "The wealth of nations and sustainable development: energy intensity and the environmental Kuznets curve." Environmental Economics 11, no. 1 (September 3, 2020): 110–23. http://dx.doi.org/10.21511/ee.11(1).2020.10.

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Scholars warn that wealth leads to unsustainable environmental development. However, over the last decades, studies have shown an increase in environmental degradation at the initial stage of economic growth, and then a decline when economic growth reaches a certain level. This first acceleration and then deceleration create an inverted U-shaped curve between pollution and economic growth, called the environmental Kuznets curve (EKC). Environmental degradation can be measured by different factors. This paper deals with two of them, i.e. energy consumption and energy intensity (EI). The latter is measured as the ratio between energy consumption and GDP. The relationship of energy consumption and intensity to economic growth can serve as a tool for examining whether an EKC exists. The paper presents continuous series of energy consumption energy intensity and gross domestic product for the Norwegian mainland economy 1835–2019. The series are used to examine the possible existence of relative and absolute environmental Kuznets curves (EKC). Time series are established using available data and annual figures for 1835–2019, which are presented for the first time. They depict a development that, first, reflects an almost constant downward trend in EI, and, second, the existence of EKCs. The paper also proposes a polynomial regression model to discuss the relationship between environmental degradation as measured by energy consumption and intensity on the one hand, and economic growth on the other. It is concluded that there are both relative and absolute EKC-relations between environmental degradation and economic growth, with 1975 as relative and 2002 as absolute turning point.

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Thuan, Nguyen, and Dang Bac Hai. "The impact of energy consumption on Carbon Intensity of Human Well-Being (CIWB)." ECONOMICS AND BUSINESS ADMINISTRATION 11, no. 1 (February 26, 2021): 19–28. http://dx.doi.org/10.46223/hcmcoujs.econ.en.11.1.1360.2021.

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A key concern when constructing sustainable development policy is reducing the negative impact on environmental systems and maximizing human welfare. In this study, we assess how energy consumption effected on Carbon intensity of human well-being (CIWB). Using two-way fixed effects in panel regression, this relationship has been investigated during 2000-2018 for 9 lower middle-income countries including Algeria, Bangladesh, Egypt, India, Morocco, Pakistan, Philippines, Uzbekistan and Vietnam, while adding GDP and FDI per capita as control variables. The study reveals that the use of energy for economic development is ineffective and inconsistent with the overview of sustainable development due to the result of increasing CIWB. However, the sign of negative coefficients of GDP and FDI per capita in control variables have given the striking findings that these factors will be helpful for lower middle - income countries to pursue sustainable development by reducing CIWB.

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Gnatyuk, M. "ENERGY EFFICIENCY OF EUROPEAN COUNTRIES AT PRESENT TIME." Bulletin of Taras Shevchenko National University of Kyiv. Geography, no. 70-71 (2018): 38–42. http://dx.doi.org/10.17721/1728-2721.2018.70.25.

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In this article, the relationship between energy consumption and GDP level has been analysed. The energy efficiency of European countries at present time based on the energy intensity of GDP and the quality of life index of the population has been explored. The efficiency level of the primary energy use through methods of system analysis and statistical calculations is determined. The relationship between the efficiency of the energy resources consumption by European states and the level of their economic development has been established. The presence of a significant imbalance in the energy intensity of GDP between European countries, namely between the economy in transition countries and developed countries of Europe has a much higher level of GDP per capita is revealed. The reason for this is that developed states of Europe have a more developed energy infrastructure in comparison with the former Soviet states. The energy-intensive and relatively powerful industrial sector consumes only a quarter of the energy resources consumed by EU countries due to its energy efficiency. Post-Soviet countries, although they consume less energy per capita, spend much more energy for own production of goods and services due to outdated transport infrastructure, poor green and renewable energy sources developing and transport, which significantly exceeds carbon dioxide and carbon monoxide emissions to the environment, therefore needs more fuel compared to transportation of developed European countries. The consistent patterns of primary energy consumption and its use by European states are revealed. Trends of reducing energy use and energy efficiency in the European countries have been analysed and considered. Energy efficiency of European countries through the quality of life index of the population, which takes into account the purchasing power index, the subsistence minimum, environmental pollution, the climate component, housing prices relative to the income of the population, time spent in traffic jams is analysed.

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Li, Shuangjie, Hongyu Diao, Liming Wang, and Chunqi Li. "Energy Efficiency Measurement: A VO TFEE Approach and Its Application." Sustainability 13, no. 4 (February 3, 2021): 1605. http://dx.doi.org/10.3390/su13041605.

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Energy efficiency is crucial to the 2030 UN Sustainable Development Goals (SDGs), but its widely measured indicator, energy intensity, is still insufficient. For this reason, in 2006, total factor energy efficiency (TFEE) was proposed with capital, labor, and energy as inputs and GDP as the desirable output. The later TFEE approach further incorporated pollution as the undesirable output. However, it is problematic to regard GDP (the total value of final products) as the desirable output, because GDP does not include the intermediate consumption, which accounts for a large part of the production activities and may even be larger than the value of GDP. GDP is more suitable for measuring distribution, while VO (value of output) is more appropriate for sustainable production analysis. Therefore, we propose a VO TFEE approach that takes VO as the desirable output instead and correspondingly incorporates the other intermediate materials and services except energy into inputs. Finally, the empirical analysis of the textile industry of EU member states during 2011–2017 indicates that the VO TFEE approach is more stable and convergent in measuring energy efficiency, and is more suitable for helping policymakers achieve the SDGs of energy saving, emissions reduction, and sustainable economic development.

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Dai, Chun Yan, Xi Liang Zhang, En Chuang Wang, Zhen Liu, Ming Hui Li, and Chun Mei Liu. "Mathematical Decomposition for Influence Factors of Unit GDP Energy Consumption and Demonstration in China." Advanced Materials Research 601 (December 2012): 437–48. http://dx.doi.org/10.4028/www.scientific.net/amr.601.437.

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Analysed various influence factors of unit GDP energy consumption, discussed the mathematical decomposition and calculation method and did empirical analysis of the influence and role on unit GDP energy consumption changes since “The Fifth Five-Year Plan”.The main conclusions are:(1) the drop of the energy efficiency is caused both by technical factors and structural factors , in which structural factors being the fundamental reason during the Eleventh Five-Year period. (2) technological energy saving is the main direct driving force of the dramatic decrease in energy intensity of China , and the alternation of structural energy saving from negative to positive is the crucial factor determining the dramatic decrease of the energy intensity of China ,and energy-saving in livelihood is a stable impetus for improving China energy efficiency improvement in the Eleventh Five-Year period .The research provided the methodological foundation for exploring the specific ways to achieve the energy efficiency goal of “The Twelfth Five-Year Plan” and also to provide a reference for the policy making of “The Twelfth Five-Year Plan” energy efficiency.

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Zhang, Jie, Majed Alharthi, Qaiser Abbas, Weiqing Li, Muhammad Mohsin, Khan Jamal, and Farhad Taghizadeh-Hesary. "Reassessing the Environmental Kuznets Curve in Relation to Energy Efficiency and Economic Growth." Sustainability 12, no. 20 (October 10, 2020): 8346. http://dx.doi.org/10.3390/su12208346.

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Energy consumption and its efficiency are significant factors for economic growth and environmental stress. This study postulates the occurrence of the Environmental Kuznets Curve hypothesis (EKC) by using the Autoregressive-Distributed Lag (ARDL) model. Furthermore, a data envelopment analysis (DEA) model is used to measure energy efficiency, energy intensity, and environment to view the trajectory of EKC for the underline economies. For this purpose, a panel dataset from 1990–2013 of 15 developing countries is analyzed to verify the objectives mentioned above. The results of the panel ARDL support EKC’s theory for underline economies, as GDP positively impacts carbon emissions, while the square of GDP is negatively related. The DEA-based results found relatively low environmental conditions in these emerging economies due to high energy intensity and low energy efficiency. This outcome suggests that renewable energy sources must be treated as an essential factor for achieving sustainable economic goals without environmental degradation.

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Pakere, Ieva, Toms Prodanuks, Agris Kamenders, Ivars Veidenbergs, Stefan Holler, Agnese Villere, and Dagnija Blumberga. "Ranking EU Climate and Energy Policies." Environmental and Climate Technologies 25, no. 1 (January 1, 2021): 367–81. http://dx.doi.org/10.2478/rtuect-2021-0027.

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Abstract The European Union (EU) has set ambitious targets to increase the overall energy efficiency and decrease the environmental impact by introducing the ‘Green Deal.’ It is an EU plan for the transition to zero greenhouse gas emissions. The overall data analyses of GHG emissions per capita and GDP value in different EU countries show that the GDP increase in 2010–2017 has not increased GHG emissions. Therefore, the link between the GDP increase through energy resource usage increase has been eliminated. However, not all of the EU 27 member states contributed to the overall EU green policy equally. The article presents the methodology for the energy and environmental performance status analyses by evaluating nine different indicators (share of renewable energy, greenhouse gases per GDP, energy intensity, primary efficiency, industry efficiency, energy consumption in households, space heating efficiency, pollutant emissions from transport and specific energy consumption of transport sector) for EU member states. Indicators have been tested through correlation analyses. The use of multidimensional Energy and climate policy indicator has been proposed to rank the performance of different EU countries. The results show that the countries with the highest score in climate and energy indicator values are Sweden, Denmark, Latvia, Austria, Finland, Ireland, and Lithuania. The lowest obtained values are Bulgaria, Poland, Hungary, the Czech Republic, and France.

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Rajneesh. "Do Trade Openness, Structure of the Economy and FDI Affect Energy Intensity in India? A Case for Including Energy Intensity as a Policy Parameter." Indian Economic Journal 65, no. 1-4 (March 2017): 172–92. http://dx.doi.org/10.1177/0019466218788438.

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This article examines the existence of a long-run relationship between energy intensity, trade openness, structure of the economy and FDI inflows in India from 1973 to 2013 using auto regressive distributive lag (ARDL) bounds test methodology. The results indicate that (a) there is a long-run cointegration among the analysed variables and (b) an increase in trade openness, share of services in gross domestic product (GDP) and share of FDI in domestic investments results in lowering energy intensity. The study also finds that the magnitude of impact of the share of industry in increasing energy intensity in India outweighs the combined energy intensity lowering impact of trade openness, share of services and share of FDI. The study validates tenets of the theory of heterogeneity of firms in international trade and pitches for including ‘energy intensity’ as a policy parameter in promoting ‘energy-frugal’ technologies via Make-in-India initiative, trade and FDI policies.

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Басовский, Leonid Basovskiy, Басовская, and Elena Basovskaya. "System Model of Long-Term Technical and Economic Development." Economics 4, no. 5 (October 10, 2016): 18–35. http://dx.doi.org/10.12737/22035.

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The results of the research of dissemination of technical and economic paradigms in developed economies are given. A system model of long-term technical and economic development is developed. The model assumes the simultaneous existence in the economy of several subsystems of different technical and economic paradigms. Each techno-economic paradigm is a new stage of development and different from the previous paradigm of higher productivity. Each subsequent industrial techno-economic paradigm provides higher productivity due to higher capital intensity and energy intensity of production. In the post-industrial techno-economic paradigms the higher performance is provided at a lower capital intensity and energy intensity of production due to a higher volume of information used. Beginning, transition to domination, the beginning of the withering away of each paradigm is accompanied by the formation of an upward half-wave of Kondratieff cycle. Econometric models of Kondratieff cycles and econometric models of real GDP per capita is obtained, provided technical and economic paradigms in developed countries. The fourth techno-economic paradigm provides the real per capita GDP value from 1929 to 3258 dollars Gehry-Hemis 1990. The fifth techno-economic paradigm provides a real GDP per capita value of 11,606 to 12,883 dollars Gehry-Hemis 1990. The sixth techno-economic paradigm provides a real GDP per capita value of 22 360 to 28 385 dollars Gehry-Hemis 1990.

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ZHU, Shouxian, Jianhua DING, and Guiyang ZHUANG. "Analysis of Energy Base for Developing a Low Carbon Economy in Guangdong." Chinese Journal of Urban and Environmental Studies 02, no. 01 (June 2014): 1450007. http://dx.doi.org/10.1142/s2345748114500079.

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On November 26, 2009, China announced to the world that China would reduce the intensity of carbon dioxide emissions per unit of GDP in 2020 by 40% to 45% compared with the level of 2005. This is "a voluntary action" taken by the Chinese government based on national conditions and was a major contribution to the global effort in tackling climate change. As a province with a large population, surging economy, and huge energy consumption, Guangdong has pioneered policy research and has run pilot projects, seeking to upgrade its industries and to explore an innovative path toward sustainable development and a low-carbon economy. Energy is a fundamental element of low-carbon development and is critical for building a low-carbon society. This paper analyzes the energy base and energy consumption patterns of Guangdong province, exploring its energy mix, self-supply ratio, energy intensity per unit GDP, energy consumption elasticity, and energy quotas for products and industries. The paper uses three low-carbon indicators — carbon productivity, energy consumption and carbon emission per capita, and energy intensity — to analyze and compare energy patterns in Guangdong and in China as a whole. Finally, the paper proposes energy demand trends along with a roadmap for low-carbon development for Guangdong. This paper can also serve as a reference for other provinces seeking low-carbon development in China.

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Bashmakov, Igor A. "Energy efficiency and economic growth." Voprosy Ekonomiki, no. 10 (October 8, 2019): 32–63. http://dx.doi.org/10.32609/0042-8736-2019-10-32-63.

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Many Russian and foreign economists are not sure, why it is essential to take efforts to improve energy efficiency in general and in Russia in particular. Unlike labour productivity improvement, energy efficiency improvements are viewed as desirable for the economic growth, yet not at all sine qua non, as economic growth is taken as mostly driven by labour and capital, with an inconspicuous shadow of energy vaguely swaying in the background. This paper aims to show the actual importance of improving energy efficiency to achieve economic growth. It highlights the contribution of energy efficiency in addressing five problems related to economic growth: removal of growth constraints by improving the affordability of energy; improvement of competitiveness; enhancement of multifactor productivity through a better ‘quality of energy’; mitigation of the natural resources scarcity; ensuring growth despite tough environmental limitations. Historically, 1 percent GDP per capita growth requires 0.5—0.8% reduction in GDP energy intensity. This latter value grows as the level of economic development increases.

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Vivid Amalia Khusna and Deni Kusumawardani. "Decomposition of Carbon Dioxide (CO2) Emissions in ASEAN Based on Kaya Identity." Indonesian Journal of Energy 4, no. 2 (August 31, 2021): 101–14. http://dx.doi.org/10.33116/ije.v4i2.122.

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ASEAN is a region with high carbon dioxide (CO2) emissions, accompanied by an increase in population, gross domestic product (GDP) and energy consumption. Population, GDP, and energy consumption can be linked to CO2 emissions through an identity equation called the Rich Identity. This research is based on Kaya identity to describe CO2 emissions to calculate the impact of population, economic activity, energy intensity and carbon intensity on CO2 emissions in ASEAN and 8 ASEAN countries (i.e., Indonesia, Malaysia, Singapore, Thailand, Philippines, Vietnam, Myanmar and Brunei Darussalam) from 1990 to 2017. The method used is the Logarithmic Mean Division Index (LMDI). The data used are from the International Energy Agency (IEA) and the World Bank. Four effects measured and main findings showed that population, economic activity and carbon intensity factor increased by 293.02 MtCO2, 790.0 MtCO2, and 195.51 MtCO2, respectively. Meanwhile, energy intensity effect made ASEAN's CO2 emissions decrease by 283.13 MtCO2. Regarding contributions to the increase in CO2 emissions in all ASEAN countries, the population effect increases CO2 emissions in all countries in ASEAN and the economic activity effect is also the same, except in Brunei Darussalam which makes CO2 emissions in this country decreased by 1.07 MtCO2. Meanwhile, the effects of energy and carbon intensity are different. The effect of energy intensity causes CO2 emissions in lower-middle income countries to decrease, while in upper-middle and high-income countries, it increases carbon emissions. In contrast to the effect of carbon intensity, that actually makes CO2 emissions increase in lower-middle income countries and reduces carbon emissions in upper-middle and high-income countries.

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Zheng, Xiaoqi, Yonglong Lu, Jingjing Yuan, Yvette Baninla, Sheng Zhang, Nils Chr Stenseth, Dag O. Hessen, Hanqin Tian, Michael Obersteiner, and Deliang Chen. "Drivers of change in China’s energy-related CO2emissions." Proceedings of the National Academy of Sciences 117, no. 1 (December 23, 2019): 29–36. http://dx.doi.org/10.1073/pnas.1908513117.

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CO2emissions are of global concern because of climate change. China has become the largest CO2emitter in the world and presently accounts for 30% of global emissions. Here, we analyze the major drivers of energy-related CO2emissions in China from 1978 when the reform and opening-up policy was launched. We find that 1) there has been a 6-fold increase in energy-related CO2emissions, which was driven primarily (176%) by economic growth followed by population growth (16%), while the effects of energy intensity (−79%) and carbon intensity (−13%) slowed the growth of carbon emissions over most of this period; 2) energy-related CO2emissions are positively related to per capita gross domestic product (GDP), population growth rate, carbon intensity, and energy intensity; and 3) a portfolio of command-and-control policies affecting the drivers has altered the total emission trend. However, given the major role of China in global climate change mitigation, significant future reductions in China’s CO2emissions will require transformation toward low-carbon energy systems.

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Dong, Yaowu, Li You, and Denghui Duan. "Clean Energy Trade Cooperation between USA and China and its Economic Impacts." E3S Web of Conferences 185 (2020): 01003. http://dx.doi.org/10.1051/e3sconf/202018501003.

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We study bilateral trade cooperation between the USA and China, along with its economic impacts. Trade Intensity Indices (TII) and Revealed Comparative Advantage indices (RCA) are investigated in six different clean energy categories including natural gas, solar, wind, biomass, hydro, and nuclear energy between 1992 and 2017. Data from TII and RCA indicate that clean energy trade cooperation between the USA and China needs to be strengthened. A Vector Autoregressive model (VAR) is established with one exogenous variable (oil price) and five endogenous variables including US TIIu, Chinese TIIc, US Gross Domestic Product (GDP), Chinese GDP and CO2 emissions. After verifying the model stationarity, impulse responses are obtained by applying positive impacts from TIIu and TIIc. The overall CO2 emissions will be reduced, and US GDP will increase. However, Chinese GDP will decrease as China is at early stages of clean energy development. To overcome the obstacles in the bilateral clean energy trade, both countries should coordinate their trade measures and devise effective policies beneficial to both countries.

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Anisimova, V. Y., E. S. Podbornova, and N. M. Tukavkin. "Energy consumption and energy intensity of the Russian GDP, taking into account the development of the transport network." IOP Conference Series: Materials Science and Engineering 918 (October 7, 2020): 012234. http://dx.doi.org/10.1088/1757-899x/918/1/012234.

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Tang, Decai, Yan Zhang, and Brandon J. Bethel. "An Analysis of Disparities and Driving Factors of Carbon Emissions in the Yangtze River Economic Belt." Sustainability 11, no. 8 (April 19, 2019): 2362. http://dx.doi.org/10.3390/su11082362.

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As one of the “three major strategies” for China’s regional development, the Yangtze River Economic Belt (YREB) is under severe pressure to reduce carbon dioxide emissions, this paper analyzes the spatiotemporal disparities, and driving factors of carbon emissions based on energy consumption and related economic development data in the YREB over the 2005–2016 11-year period. Using the Stochastic Impacts Regression on Population, Affluence and Technology (STIRPAT) model, we empirically test the factors affecting YREB carbon emissions and key drivers in various provinces and municipalities. The main findings are as follows. First, per capita GDP, both industrial structure and energy intensity have positive effects on increasing carbon emissions. Second, per capita GDP and energy intensity have the largest impact on the increase of carbon emissions, and the urbanization rate has the largest inhibitory effect on carbon emissions.

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Xue, Li-Ming, Shuo Meng, Jia-Xing Wang, Lei Liu, and Zhi-Xue Zheng. "Influential Factors Regarding Carbon Emission Intensity in China: A Spatial Econometric Analysis from a Provincial Perspective." Sustainability 12, no. 19 (October 1, 2020): 8097. http://dx.doi.org/10.3390/su12198097.

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Emission reduction strategies based on provinces are key for China to mitigate its carbon emission intensity (CEI). As such, it is valuable to analyze the driving mechanism of CEI from a provincial view, and to explore a coordinated emission mitigation mechanism. Based on spatial econometrics, this study conducts a spatial-temporal effect analysis on CEI, and constructs a Spatial Durbin Model on the Panel data (SDPM) of CEI and its eight influential factors: GDP, urbanization rate (URB), industrial structure (INS), energy structure (ENS), energy intensity (ENI), technological innovation (TEL), openness level (OPL), and foreign direct investment (FDI). The main findings are as follows: (1) overall, there is a significant and upward trend of the spatial autocorrelation of CEI on 30 provinces in China. (2) The spatial spillover effect of CEI is positive, with a coefficient of 0.083. (3) The direct effects of ENI, ENS and TEL are significantly positive in descending order, while INS and GDP are significantly negative. The indirect effects of URB and ENS are significantly positive, while GDP, ENI, OPL and FDI are significantly negative in descending order. Economic and energy-related emission reduction measures are still crucial to the achievement of CEI reduction targets for provinces in China.

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Qin, Jiancheng, Hui Tao, Minjin Zhan, Qamar Munir, Karthikeyan Brindha, and Guijin Mu. "Scenario Analysis of Carbon Emissions in the Energy Base, Xinjiang Autonomous Region, China." Sustainability 11, no. 15 (August 5, 2019): 4220. http://dx.doi.org/10.3390/su11154220.

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The realization of carbon emissions peak is important in the energy base area of China for the sustainable development of the socio-economic sector. The STIRPAT model was employed to analyze the elasticity of influencing factors of carbon emissions during 1990–2010 in the Xinjiang autonomous region, China. The results display that population growth is the key driving factor for carbon emissions, while energy intensity is the key restraining factor. With 1% change in population, gross domestic product (GDP) per capita, energy intensity, energy structure, urbanization level, and industrial structure, the change in carbon emissions was 0.80%, 0.48%, 0.20%, 0.07%, 0.58%, and 0.47%, respectively. Based on the results from regression analysis, scenario analysis was employed in this study, and it was found that Xinjiang would be difficult to realize carbon emissions peak early around 2030. Under the condition of the medium-high change rates in energy intensity, energy structure, industrial structure, and with the low-medium change rates in population, GDP per capita, and urbanization level, Xinjiang will achieve carbon emissions peak at of 626.21, 636.24, 459.53, and 662.25 million tons in the year of 2030, 2030, 2040, and 2040, respectively. At last, under the background of Chinese carbon emissions peak around 2030, this paper puts forward relevant policies and suggestions to the sustainable socio-economic development for the energy base area, Xinjiang autonomous region.

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Wysokiński, Marcin, Arkadiusz Gromada, Magdalena Golonko, and Paulina Trębska. "ENERGY INTENSITY OF ECONOMIES IN THE EUROPEAN UNION AND THE WORLD." Annals of the Polish Association of Agricultural and Agribusiness Economists XXII, no. 2 (May 26, 2020): 219–27. http://dx.doi.org/10.5604/01.3001.0014.1551.

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The technological nature of human existence depends on the energy that has become a condition for the existence of every civilization and the driving force of every action. This confirms the modern dependence of humanity on energy, which determines economic growth and standard of living. It can also be a source of international conflicts. One of the main problems is the limited nature of its sources, especially non-renewable ones. Today, energy is a key factor in the development of the World and countries, characterized by different effectiveness of its use. Therefore, the main objective of the article was to assess the energy intensity of EU and world economies. World leaders in this field and countries with the highest energy consumption per unit of GDP were presented. The structure of energy sources in EU countries was also analyzed. It was found that 4 countries with the highest energy consumption account for 51% of global consumption, which indicates a very high level of concentration.

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Arango-Miranda, Raúl, Robert Hausler, Rabindranarth Romero-Lopez, Mathias Glaus, and Sara Ibarra-Zavaleta. "Carbon Dioxide Emissions, Energy Consumption and Economic Growth: A Comparative Empirical Study of Selected Developed and Developing Countries. “The Role of Exergy”." Energies 11, no. 10 (October 7, 2018): 2668. http://dx.doi.org/10.3390/en11102668.

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Diverse factors may have an impact in carbon dioxide (CO2) emissions; thus, three main contributors, energy consumption, gross domestic product (GDP) and an exergy indicator are examined in this work. This study explores the relationship between economic growth and energy consumption by means of the hypothesis postulated for the Environmental Kuznets Curve (EKC). Panel data for ten countries, from 1971 to 2014 have been studied. Despite a wide gamma of research on the EKC, the role of an exergy variable has not been tested to find the EKC; for this reason, exergy analysis is proposed. Exergy analyses were performed to propose an exergetic indicator as a control variable and a comparative empirical study is developed to study a multivariable framework with the aim to detect correlations between them. High correlation between CO2, GDP, energy consumption, energy intensity and trade openness are observed, on the other hand not statistically significant values for trade openness and energy intensity. The results do not support the EKC hypothesis, however exergy intensity opens the door for future research once it proves to be a useful control variable. Exergy provides opportunities to analyze and implement energy and environmental policies in these countries, with the possibility to link exergy efficiencies and the use of renewables.

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Kurmanov, Nurlan, Ulukbek Aliyev, Aizhan Satbayeva, Gulmira Kabdullina, and Darkhan Baxultanov. "ENERGY INTENSITY OF KAZAKHSTAN’S GDP: FACTORS FOR ITS DECREASE IN A RESOURCE-EXPORT DEVELOPING ECONOMY." International Journal of Energy Economics and Policy 10, no. 5 (August 10, 2020): 447–53. http://dx.doi.org/10.32479/ijeep.9817.

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Wang, Lun, Zhao Sun, Zhuang Li, Wen Jin Zhao, and Yu Li. "An Optimal Model for Carbon Dioxide Emission Control in the Low-Carbon Urban Agglomeration Based on Sustainable Development of Economy, Society and Environment (2): A Case Study." Advanced Materials Research 610-613 (December 2012): 970–74. http://dx.doi.org/10.4028/www.scientific.net/amr.610-613.970.

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Based on an urban agglomeration regional planning in 12th Five-Year Planning , selected two indicators of carbon intensity, energy intensity that were required by the regional planning, this paper developed an optimal model of low-carbon urban agglomeration on the base of sustainable development of economy, society and environment. The case study shows that the carbon emission level of urban agglomeration is 1.8×107 tons in 2015, and the carbon intensity was decreased by 19.00% and energy intensity was reduced by 39.17% compared with those in 2010; meanwhile, the carbon intensity and energy intensity in the core area was reduced by 40.00% and 41.86% respectively compared with those in 2010 subject to the conditions of carbon intensity, carbon sink area, energy intensity, GDP and so on. The optimized scheme could not only meet the requirements of carbon intensity decreased by 17.00%, energy intensity reduced by 16.00% in 2015 compared with those in 2010 proposed by 12th Five-Year Planning Outline of Controlling Greenhouse Gas Emission, but also complied with the requirements of carbon intensity decreased by 18.00% and energy intensity reduced by 20.00% of regional planning targets. The established model also provided more decision-making space for the sustainable development of low-carbon urban agglomeration.

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Sahlian, Daniela Nicoleta, Adriana Florina Popa, and Raluca Florentina Creţu. "Does the Increase in Renewable Energy Influence GDP Growth? An EU-28 Analysis." Energies 14, no. 16 (August 5, 2021): 4762. http://dx.doi.org/10.3390/en14164762.

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The aim of our study was to analyze whether the increase in the use of renewable energy can help GDP growth. The research carried out shows that renewable energy has the ability to decrease or neutralize the negative impact of greenhouse gases (GHG), but also to maintain economic growth. We focused our analysis on the EU-28 as we know that the EU Commission’s aim, in the near future, is to join forces to reduce the GHG used and move to renewable sources. We used a panel analysis with data between 2000 and 2019 from all Member States, and our results showed that their economic growth is influenced positively by the production of renewable energy, the GHG per capita, and the GHG intensity per GDP.

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Xue, Yixi, Jie Ren, and Xiaohang Bi. "Impact of Influencing Factors on CO2 Emissions in the Yangtze River Delta during Urbanization." Sustainability 11, no. 15 (August 2, 2019): 4183. http://dx.doi.org/10.3390/su11154183.

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The Yangtze River Delta (YRD) is China’s largest urban agglomeration with a rapid urbanization process. This paper analyzes the dynamic relationship between urbanization rate, energy intensity, GDP per capita, and population with CO2 emissions in YRD over 1990–2011 based on the extended STIRPAT model, impulse response function, and variance decomposition. A support vector machine model was constructed to further predict the scenarios of YRD’s CO2 emissions from 2015–2020. The results show that YRD’s CO2 emissions continuously increased during the sample period and are predicted to increase over 2015–2020. Energy intensity is the most influential factor, both in the short and long term, and the total population contributes the least. However, the influencing magnitude of energy intensity tends to decrease in the long term. The increase of urbanization rate is still accompanied by the increase of CO2 emissions in YRD, but an inverted-U shape relationship between them may exist in the long term. The contribution of GDP per capita to CO2 emissions is higher than the population and urbanization rate, and its contribution rate for CO2 emissions is growing. The Kuznets curve does not exist in the current YRD.

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Zhao, Wen Jin, Lun Wang, Zhao Sun, Zhuang Li, and Yu Li. "An IFP Model for Carbon Footprint in Low-Carbon Urban Agglomeration under Uncertainty." Advanced Materials Research 663 (February 2013): 936–40. http://dx.doi.org/10.4028/www.scientific.net/amr.663.936.

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This paper corrected the existing optimization model of low-carbon urban agglomeration using interval fuzzy programming (IFP) method and several constraint conditions are revised according to the 12th Five Year Plan of the urban agglomeration. The case study shows that the carbon footprint of per unit GDP of urban agglomeration was decreased by [21.95, 57.32] (%) and energy intensity was reduced by [25.89, 50.81] (%) compared with those in 2010; meanwhile, the carbon footprint of per unit GDP and energy intensity in the core area was reduced by [18.90, 34.67] (%) and [22.36, 22.76] (%) respectively, compared with those in 2010. The optimized scheme complies with the requirements of the 12th Five-Year Planning Outline of Controlling Greenhouse Gas Emission and the regional planning targets. The corrected model also provided more decision-making space for the sustainable development of low-carbon urban agglomeration.

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Wilarnugroho, Bagus, and Sri Herianingrum. "Pengaruh Intensitas Konsumsi Energi (IKE) Dan Akses Air Bagi Produk Domestik Bruto Negara-Negara Organisasi Kerjasama Islam (OKI)." Jurnal Ekonomi Syariah Teori dan Terapan 3, no. 12 (February 20, 2017): 960. http://dx.doi.org/10.20473/vol3iss201612pp960-972.

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Energy use intensity (EUI) and water access are vital to economic activities. World energy need is growing meanwhile the energy resource couldn’t follow it. Futhermore, world fresh water quantity is declining.This research is aim to acknowledge whether there is an impact of EUI and water access on gross domestic products (GDP) in Organization of Islamic Cooperation (OIC) member states. The research is using World Bank data with quantitative approach. The data had been running using panel data regression method. The data are from Indonesia, Malaysia, Pakistan and Bangladesh which consist of EUI and water access data as an independent variables and GDP as a dependent varible. According to the results, seen that EUI and water access have a sigificant impact, partialy and simultaneously, to GDP within four OIC member. Therefore, we can conclude that the EUI and water access are able to increase GDPof OIC member states.

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Gaweł, Bartłomiej, and Andrzej Paliński. "Long-Term Natural Gas Consumption Forecasting Based on Analog Method and Fuzzy Decision Tree." Energies 14, no. 16 (August 11, 2021): 4905. http://dx.doi.org/10.3390/en14164905.

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Classic forecasting methods of natural gas consumption extrapolate trends from the past to subsequent periods of time. The paper presents a different approach that uses analogues to create long-term forecasts of the annual natural gas consumption. The energy intensity (energy consumption per dollar of Gross Domestic Product—GDP) and gas share in energy mix in some countries, usually more developed, are the starting point for forecasts of other countries in the later period. The novelty of the approach arises in the use of cluster analysis to create similar groups of countries and periods based on two indicators: energy intensity of GDP and share of natural gas consumption in the energy mix, and then the use of fuzzy decision trees for classifying countries in different years into clusters based on several other economic indicators. The final long-term forecasts are obtained with the use of fuzzy decision trees by combining the forecasts for different fuzzy sets made by the method of relative chain increments. The forecast accuracy of our method is higher than that of other benchmark methods. The proposed method may be an excellent tool for forecasting long-term territorial natural gas consumption for any administrative unit.

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Zhou, Jinjin, Zenglin Ma, Taoyuan Wei, and Chang Li. "Threshold Effect of Economic Growth on Energy Intensity— Evidence from 21 Developed Countries." Energies 14, no. 14 (July 12, 2021): 4199. http://dx.doi.org/10.3390/en14144199.

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Based on threshold regression models, this paper analyzes the effect of economic growth on energy intensity by using panel data from 21 developed countries from 1996 to 2015. Results show that a 1% increase in GDP per capita can lead to a 0.62–0.78% reduction in energy intensity, implying economic growth can significantly reduce energy intensity. The extent of the reduction in energy intensity varies depending on the economic development stages represented by key influencing factors including energy mix in consumption, urbanization, industrial structure, and technological progress. Specifically, the reduction in energy intensity due to economic growth can be enhanced with relatively more renewable energy consumption and more urban population until a threshold point, where the enhancement disappears. On the other hand, the extent of the energy intensity reduction due to economic growth can be weakened with relatively more tertiary industry activities and more research and development (R&D) investment in an economy until a threshold point, where the weakening cannot continue. However, compared to the early stages represented by the low ends of renewable energy consumption, urban population, tertiary industry activities, and R&D investment, the later stages represented by the high ends of these key factors after a threshold show the weakened effect of economic growth on the decline of energy intensity. Hence, when an economy is well-developed, policy makers are advised to put fewer expectations on the role of economic growth to reduce energy intensity, while pursuing relatively cleaner energy, greater urbanization, more tertiary industry activities, and advanced technologies.

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Hatzigeorgiou, Emmanouil, Heracles Polatidis, and Dias Haralambopoulos. "CO2 emissions, GDP and energy intensity: A multivariate cointegration and causality analysis for Greece, 1977–2007." Applied Energy 88, no. 4 (April 2011): 1377–85. http://dx.doi.org/10.1016/j.apenergy.2010.10.008.

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Agovino, Massimiliano, Silvana Bartoletto, and Antonio Garofalo. "Modelling the relationship between energy intensity and GDP for European countries: An historical perspective (1800–2000)." Energy Economics 82 (August 2019): 114–34. http://dx.doi.org/10.1016/j.eneco.2018.02.017.

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Jiang, Wanbei, and Weidong Liu. "Provincial-Level CO2 Emissions Intensity Inequality in China: Regional Source and Explanatory Factors of Interregional and Intraregional Inequalities." Sustainability 12, no. 6 (March 23, 2020): 2529. http://dx.doi.org/10.3390/su12062529.

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As the largest emitter in the world, China has pledged to reduce CO2 emissions intensity (CO2 emissions per unit of output) by 60–65% between 2005 and 2030. CO2 emissions intensity inequality analysis in China can provide a scientific basis for the Chinese government to formulate reasonable regional carbon emission abatement strategies, so as to realize the goal above. This paper adopted the Theil index to study the provincial-level CO2 emissions intensity inequality in China during 2005–2015. The regional decomposition was firstly conducted and then the factors of interregional and intraregional inequalities were explored. The results show: (i) a clear increase in provincial CO2 emissions intensity inequality in China has happened; (ii) this inequality and its increase were both mainly explained by the intraregional component; and (iii) the energy efficiency was the most important and positive contributor in the interregional, Eastern, Central, and Western China inequalities. Energy efficiency was also the key factor that caused the growth in interregional and Western China inequalities. However, most of the Eastern and Central China inequality increments over the whole period were respectively driven by the expanding carbonization gap and the changing GDP share, instead of the trajectory of energy efficiency. According to the results, regional emission mitigation strategies were proposed.

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Nkomo, Jabavu Clifford. "Crude oil price hikes and issues for energy security for Southern Africa." Journal of Energy in Southern Africa 21, no. 2 (May 1, 2010): 12–16. http://dx.doi.org/10.17159/2413-3051/2010/v21i2a3251.

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This paper addresses a number of issues related to crude oil prices, focusing on Southern Africa. It begins by analysing oil price movements from 1970 to 2008, and examines various factors that may have contributed to the sharp rise and fall in prices. A characteristic feature in the oil market is the time lags it takes to react to price changes. A high oil intensity of GDP makes the economy vulnerable to oil price increases, so that countries with a high oil/GDP ratio are harder hit than others. There are two main issues for energy security: first, on whether the potential use of the oil weapon can be taken seriously; and second, how to minimize vulnerability to oil supply shocks by reducing oil dependence and by a developing or enlarging a strategic stockpile of oil.

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Fazli, Parto, and Ebrahim Abbasi. "Analysis of the Validity of Kuznets Curve of Energy Intensity among D-8 Countries: Panel-ARDL Approach." International Letters of Social and Humanistic Sciences 81 (April 2018): 1–12. http://dx.doi.org/10.18052/www.scipress.com/ilshs.81.1.

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The objective of the study is to test experimentally the Kuznets curve of energy intensity in selected developing countries (Iran, Turkey, Malaysia, Pakistan, Egypt, Bangladesh, Indonesia and Nigeria) with the focus of D-8 countries during 1990-2014. According to the results, and by using the static and dynamic estimators and the Panel- ARDL model, the Kuznets curve was accepted for energy intensity and the per capita income threshold was estimated $3931.25. The urbanization rate and the degree of industrialization have a positive and significant effect on the GDP of consuming energy of D-8 countries in the long term. The most important policy recommendations were discussed for policy-makers and researchers.

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Journal articles on the topic 'GDP ENERGY INTENSITY'

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