Electricity consumption and economic growth nexus in Beijing: A causal analysis of quarterly sectoral data

Da, Liu; Ruan, Ling; Liu, Jinchen; Huang, Han; Zhang, Guowei; Feng, Yi; Li, Ying

doi:10.1016/j.rser.2017.09.016

Cited by 48 publications

(20 citation statements)

References 33 publications

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“…Lenzen et al ( 2018 ) found that the world’s carbon emissions increased from 3.9 to 4.5 GtCO 2 e between 2009 and 2013 and that international tourism accounts for about 8% of the world’s greenhouse gas emissions. Addressing the environmental degradation from the carbon emissions that are adversely associated with economic growth and sustainable efforts is required to preserve the environment (Azam 2016 ; Bah and Azam 2017 ; Liu et al 2018 ; Ozcan and Ozturk 2019 ; Rafindadi and Ozturk 2017 ; Zaidi et al 2019 ). The tourism sector accounts for 5% of the world’s carbon dioxide (CO 2 ) emissions.…”

Section: Introductionmentioning

confidence: 99%

The dynamic links among energy consumption, tourism growth, and the ecological footprint: the role of environmental quality in 38 IEA countries

Khan

Hou

2020

Environ Sci Pollut Res

185

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We examine the impact of energy consumption and tourism growth on the ecological footprints and economic growth of 38 International Energy Agency (IEA) countries, as moderated by labor and capital, over the 1995-2018 period. We develop a comprehensive empirical analysis that applies second-generation unit root and cross-section dependence analysis. The cointegration analysis indicates long-run relationships among the variables, while the fully modified least square (FMOLS) approach specifies that energy consumption promotes economic growth and degrades environmental quality in the long run, and tourism growth improves environmental quality and stimulates economic growth in the long run. In addition, the result of a pairwise Granger causality test reveals bidirectional causality between energy consumption and economic growth and unidirectional causality from the ecological footprint to energy consumption. Policy implications for theory and practice and directions for future research in the area are presented.

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Section: Introductionmentioning

confidence: 99%

The dynamic links among energy consumption, tourism growth, and the ecological footprint: the role of environmental quality in 38 IEA countries

Khan

Hou

2020

Environ Sci Pollut Res

185

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“…Kahouli [10], Afzal et al [11] and Asumadu-Sarkodie and Owusu [12] applied the same method for different countries and reached similar results. On the other hand, Liu et al [13] also reported that a causal relationship is identified between these factors using Granger and Toda Yamamoto causality analyzes. In addition, Iyke [14], Mezghani and Haddad [15], Sbia et al [16] and Ibrahiem [17] also took this issue into consideration using different methods such as the Vector Error Correction Model (VECM), Johansen Cointegration and the Autoregressive Distributed Lag Bound Test (ARDL).…”

Section: Literature Reviewmentioning

confidence: 99%

The Effects of Electricity Production on Industrial Development and Sustainable Economic Growth: A VAR Analysis for BRICS Countries

et al. 2019

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This study aims to evaluate the effect of electricity production on industrial development and sustainable economic growth. In this context, Brazil, Russia, India, China, and South Africa (BRICS), countries which have the highest increase in electricity production in the period of 2000-2018, are included in the scope of this study. Annual data of these variables in the period of 1991-2018 are used and three different models are created by using Vector Auto Regression (VAR) methodology. The findings state that electricity production in BRICS countries has a positive effect on both industrial production and sustainable economic growth. Hence, electricity production needs to be increased for them. For this purpose, it is important to encourage investors with tax advantages, location orientation and financing. Moreover, BRICS countries should give importance to renewable energy investments in order to increase electricity production. These issues have a contributing effect to sustainable economic growth.

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“…Additionally, for sustainability of the power industrial business, an accurate electricity consumption forecasting model can be used to adjust the production and consumption patterns of electricity. It can also support decisions of energy management policy, such as load unit commitment, the operational security of electrical plants and power systems, economic load dispatching, and energy marketing [11,12].…”

Section: Introductionmentioning

confidence: 99%

Using the LSTM Network to Forecast the Demand for Electricity in Poland

Manowska

2020

Applied Sciences

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The impact of environmental regulations introduced by the European Union is of key importance for electricity generation systems. The Polish fuel structure of electricity production is based on solid fuels. Moreover, the generating base is outdated and must gradually be withdrawn from the power system. In this context, Poland’s energy policy is undergoing a transformation as climate and environmental regulations are becoming increasingly stringent for the energy sector based on solid fuels (hard coal and lignite). However, the transformation process must be adapted to market demands, because the overriding goal is to ensure energy security by maintaining the continuity of energy supplies and an acceptable electricity price. This directly contributes to the development of the entire economy and the standard of living of the society, in accordance with the European Agreement establishing an association between the Republic of Poland and the European Communities and their Member States, signed on 16 December 1991, and the European Energy Charter, signed on 17 December 1991. Ensuring energy security is the most important goal of the energy policy. Therefore, energy companies must forecast the demand. The main goal of this article is to develop a mathematical model of electricity consumption by 2040 by all sectors of the economy: industry, transport, residential, commercial and public services, agriculture, forestry, and fishing. In order to achieve the intended goal, a model was developed by using Long Short-Term Memory (LSTM) artificial neural networks, which belong to deep learning techniques and reflect long-term relationships in time series for a small set of statistical data. The results show that the proposed model can significantly improve the accuracy of forecasts (1–3% of mean absolute percentage error (MAPE) for the analyzed sectors of the economy).

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Electricity consumption and economic growth nexus in Beijing: A causal analysis of quarterly sectoral data

Cited by 48 publications

References 33 publications

The dynamic links among energy consumption, tourism growth, and the ecological footprint: the role of environmental quality in 38 IEA countries

The dynamic links among energy consumption, tourism growth, and the ecological footprint: the role of environmental quality in 38 IEA countries

The Effects of Electricity Production on Industrial Development and Sustainable Economic Growth: A VAR Analysis for BRICS Countries

Using the LSTM Network to Forecast the Demand for Electricity in Poland

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