scholarly journals Energy Crisis in Pakistan and Economic Progress: Decoupling the Impact of Coal Energy Consumption in Power and Brick Kilns

Mathematics ◽  
2021 ◽  
Vol 9 (17) ◽  
pp. 2083
Author(s):  
Abdul Rehman ◽  
Hengyun Ma ◽  
Magdalena Radulescu ◽  
Crenguta Ileana Sinisi ◽  
Zahid Yousaf
Keyword(s):  
Energy Consumption ◽  
Quantile Regression ◽  
Least Squares ◽  
Alternative Energy ◽  
Energy Crisis ◽  
Series Data ◽  
Power Sector ◽  
Brick Kilns ◽  
Economic Progress ◽  
The Impact

This study aims to examine the impact of coal energy consumption on the economic progress in Pakistan by using annual time series data during 1972–2019. Three-unit root tests were employed to rectify the variables’ stationarity. The quantile regression approach with the extension of cointegration regression test was utilized to check the variables interaction with the economic progress. The outcomes of the quantile regression uncover that coal energy consumption in power sector and coal energy consumption in brick kilns have adverse influence to the economic progress, while total coal energy consumption has a productive association with the economic progress. Similarly, the findings of cointegration regression analysis uncover that via FMOLS (Fully Modified Least Squares) and DOLS (Dynamic Least Squares) that variables coal energy consumption in power sector and brick kilns have an adverse connection with the economic progress, while total coal energy consumption uncover a productive linkage to the economic progress in Pakistan. Pakistan is still facing a deep energy crisis because of the lack of energy production from cheap sources. New possible policies are required in this direction to improve the energy sector by paying more attention to the alternative energy sources to foster the economic progress.

scholarly journals The Impact of Industrialization, Trade Openness, Financial Development, and Energy Consumption on Economic Growth in Indonesia

Economies ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 174
Author(s):  
Khalid Eltayeb Elfaki ◽  
Rossanto Dwi Handoyo ◽  
Kabiru Hannafi Ibrahim
Keyword(s):  
Economic Growth ◽  
Energy Consumption ◽  
Least Squares ◽  
Financial Development ◽  
Correction Term ◽  
Trade Openness ◽  
Ordinary Least Squares ◽  
Distributed Lag ◽  
Long Run ◽  
The Impact

This study aimed to scrutinize the impact of financial development, energy consumption, industrialization, and trade openness on economic growth in Indonesia over the period 1984–2018. To do so, the study employed the autoregressive distributed lag (ARDL) model to estimate the long-run and short-run nexus among the variables. Furthermore, fully modified ordinary least squares (FMOLS), dynamic least squares (DOLS), and canonical cointegrating regression (CCR) were used for a more robust examination of the empirical findings. The result of cointegration confirms the presence of cointegration among the variables. Findings from the ARDL indicate that industrialization, energy consumption, and financial development (measured by domestic credit) positively influence economic growth in the long run. However, financial development (measured by money supply) and trade openness demonstrate a negative effect on economic growth. The positive nexus among industrialization, financial development, energy consumption, and economic growth explains that these variables were stimulating growth in Indonesia. The error correction term indicates a 68% annual adjustment from any deviation in the previous period’s long-run equilibrium economic growth. These findings provide a strong testimony that industrialization and financial development are key to sustained long-run economic growth in Indonesia.

The impact of financial development, economic growth and energy consumption on environmental degradation

2015 ◽  
Vol 26 (5) ◽  
pp. 666-682 ◽  
Author(s):  
Madhu Sehrawat ◽  
A K Giri ◽  
Geetilaxmi Mohapatra
Keyword(s):  
Economic Growth ◽  
Energy Consumption ◽  
Financial Development ◽  
Environmental Degradation ◽  
Series Data ◽  
Development Economic ◽  
Content Type ◽  
Indian Economy ◽  
Long Run ◽  
The Impact

Purpose – The purpose of this paper is to investigate the impact of financial development, economic growth and energy consumption on environment degradation for Indian economy by using the time series data for the period 1971-2011. Design/methodology/approach – The stationary properties of the variables are checked by ADF, DF-GLS, PP and Ng-Perron unit root tests. The long-run relationship is examined by implementing the Autoregressive Distributed Lag bounds testing approach to co-integration and error correction method (ECM) is applied to examine the short-run dynamics. The direction of the causality is checked by VECM framework and variance decomposition is used to predict exogenous shocks of the variables. Findings – The empirical evidence confirms the existence of long-run relationship among the variables. Financial development appears to increase environmental degradation in India. The main contributors to environmental degradation are: economic growth, energy consumption financial development and urbanization. The results also lend support to the existence of environmental Kuznets curves for Indian economy. Research limitations/implications – The present study suggests that environmental degradation can be reduced at the cost of economic growth or energy efficient technologies should be encouraged to enhance the domestic product with the help of financial sector by improving environmental friendly technologies from advanced economies. Originality/value – This paper proposes to make a contribution to the existing literature through examining the relationship between financial development and environmental degradation in Indian economy during 1971-2011 by employing modern econometric techniques.

scholarly journals Extreme return, extreme volatility and investor sentiment

Filomat ◽  
2016 ◽  
Vol 30 (15) ◽  
pp. 3949-3961 ◽  
Author(s):  
Xu Gong ◽  
Fenghua Wen ◽  
Zhifang He ◽  
Jia Yang ◽  
Xiaoguang Yang ◽  
...  
Keyword(s):  
Linear Regression ◽  
Quantile Regression ◽  
Regression Model ◽  
Least Squares ◽  
Linear Regression Model ◽  
Investor Sentiment ◽  
Generalized Least Squares ◽  
Regression Methods ◽  
Leading Role ◽  
The Impact

The extreme return and extreme volatility have great influences on the investor sentiment in stock market. However, few researchers have taken the phenomenon into consideration. In this paper, we first distinguish the extreme situations from non-extreme situations. Then we use the ordinary generalized least squares and quantile regression methods to estimate a linear regression model by applying the standardized AAII, the return and volatility of SP 500. The results indicate that, except for extremely negative return, other return sequences can cause great changes in investor sentiment, and non-extreme return plays a leading role in affecting the overall American investor sentiment. Extremely positive (negative) return can rapidly improve (further reduce) the level of investor sentiment when investors encounter extremely pessimistic situations. The impact gradually decreases with improvement of the sentiment until the situation turns optimistic. In addition, we find that extreme and non-extreme volatility cannot a_ect the overall investor sentiment.

scholarly journals Renewable Energy Consumption and Economic Growth in Asia Pacific

2021 ◽  
Author(s):  
Pisi Bethania Titalessy
Keyword(s):  
Economic Growth ◽  
Renewable Energy ◽  
Energy Consumption ◽  
Alternative Energy ◽  
Panel Data Analysis ◽  
Environmentally Friendly ◽  
Asia Pacific ◽  
Environmental Damage ◽  
Renewable Energy Consumption ◽  
The Impact

The problem of climate change is increasingly global and results in environmental damage due to the use of fossil energy in human activities. An increasing population will make energy consumption increase and can make things worse. Therefore, it is necessary to replace old energy with alternative energy that is more environmentally friendly and makes productivity effective and efficient. Renewable energy is pointed out as an alternative energy source that is environmentally friendly and the process is sustainable because it is always available in nature. Renewable energy is expected to increase the country's national income. This study aims to analyze the impact of renewable energy on economic growth in the Asia Pacific region as a whole. By using data from 2000-2015, panel data analysis in this study shows that Renewable Energy Consumption (REC) has a negative and significant relationship to economic growth, while renewable energy and combustible waste (CRW) has a significant and positive effect on economic growth.

scholarly journals Multi-Scenario Analysis of Energy Consumption and Carbon Emissions: The Case of Hebei Province in China

Energies ◽  
2019 ◽  
Vol 12 (4) ◽  
pp. 624 ◽  
Author(s):  
Zeng Li ◽  
Jingying Fu ◽  
Gang Lin ◽  
Dong Jiang ◽  
Kun Liu ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Alternative Energy ◽  
Ghg Emissions ◽  
Structure Optimization ◽  
Energy System ◽  
Hebei Province ◽  
Energy Structure ◽  
Reference Scenario ◽  
Low Carbon ◽  
The Impact

In view of the complexity of the energy system and its complex relationship with socio-economic factors, this study adopts the Long-range Energy Alternative Planning (LEAP) model, a technology-based, bottom-up approach, scenario-based analysis, to develop a systematic analysis of the current and future energy consumption, supply and associated Green House Gas (GHG) emissions from 2015 to 2050. The impact of various energy policies on the energy system in Hebei Province was analysed by considering four scenarios: a Reference Scenario (REF), Industrial Structure Optimization Scenario (ISO), Terminal Consumption Structure Optimization Scenario (TOS) and Low-carbon Development Scenario (LCD). By designing strategic policies from the perspective of industrial adjustment, aggressive energy structure policies and measures, such as the ISO and the TOS, and even more aggressive options, such as the LCD, where the percentage of cleaner alternative energy sources has been further increased, it has been indicated that energy consumption will have increased from 321.618 million tonnes of coal equivalent (Mtce) in 2015 to 784.88 Mtce in 2050 in the REF, with a corresponding increase in GHG emissions from 920.56 million metric tonnes (Mt) to 2262.81 Mt. In contrast, the more aggressive policies and strategies involved in the LCD, which combines the ISO with the policy-oriented TOS, can lower energy consumption by 50.82% and CO2 emissions by 64.26%. The results shed light on whether and how these scenarios can shape the energy-carbon emission reduction trajectories and develop the low-carbon pathways in Hebei Province.

scholarly journals Renewable Energy Consumption and Economic Growth in Asia Pacific

2021 ◽  
Vol 4 (2) ◽  
Author(s):  
Pisi Bethania Titalessy ◽  
Keyword(s):  
Economic Growth ◽  
Renewable Energy ◽  
Energy Consumption ◽  
Alternative Energy ◽  
Panel Data Analysis ◽  
Environmentally Friendly ◽  
Asia Pacific ◽  
Environmental Damage ◽  
Renewable Energy Consumption ◽  
The Impact

The problem of climate change is increasingly global and results in environmental damage due to the use of fossil energy in human activities. An increasing population will make energy consumption increase and can make things worse. Therefore, it is necessary to replace old energy with alternative energy that is more environmentally friendly and makes productivity effective and efficient. Renewable energy is pointed out as an alternative energy source that is environmentally friendly and the process is sustainable because it is always available in nature. Renewable energy is expected to increase the country's national income. This study aims to analyze the impact of renewable energy on economic growth in the Asia Pacific region as a whole. By using data from 2000-2015, panel data analysis in this study shows that Renewable Energy Consumption (REC) has a negative and significant relationship to economic growth, while renewable energy and combustible waste (CRW) has a significant and positive effect on economic growth.

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 Do Financial Development and Economic Openness Matter for Economic Progress in an Emerging Country? Seeking a Sustainable Development Path

2021 ◽  
Vol 14 (6) ◽  
pp. 237
Author(s):  
Ammara Hussain ◽  
Ammar Oad ◽  
Munir Ahmad ◽  
Muhammad Irfan ◽  
Farhan Saqib
Keyword(s):  
Financial Development ◽  
Emerging Economies ◽  
Least Square ◽  
Series Data ◽  
Economic Openness ◽  
Economic Progress ◽  
Cointegration Tests ◽  
The Impact ◽  
The Relationship

While emerging economies face the challenge of competing with developed nations, they are capable of catching up to the developed world. In this context, financial development and the degree of economic openness may provide better living conditions for the current generation without giving up future generations’ prosperity. Therefore, this research’s prime intention is to investigate the impact of economic openness and financial development on economic progress, employing Pakistan’s time-series data from 1975–2018. To examine the long-term association between economic openness, financial development, and economic progress, Autoregressive Distributed Lag (ARDL) cointegration tests were performed and the results present a long-term association between these variables. Findings from ARDL estimates indicate that the relationship between financial development and economic progress is significantly positive in the long term. Contrastingly, the relationship between economic openness and economic progress is significantly positive in the short term. A fully modified ordinary least square technique was applied to check the robustness of the long-term links. The Granger causality test revealed that economic progress is motivated by both economic openness and financial development in an emerging economy such as Pakistan. Thus, policies boosting financial development and economic openness are proposed to put the emerging economies on a path of sustainable economic development.

scholarly journals A Synchronous Prediction Model Based on Multi-Channel CNN with Moving Window for Coal and Electricity Consumption in Cement Calcination Process

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4284
Author(s):  
Xin Shi ◽  
Gaolu Huang ◽  
Xiaochen Hao ◽  
Yue Yang ◽  
Ze Li
Keyword(s):  
Energy Consumption ◽  
Time Series Data ◽  
Production Optimization ◽  
Cement Industry ◽  
Channel Structure ◽  
Series Data ◽  
Time Lags ◽  
Moving Window ◽  
Coal Consumption ◽  
The Impact

The precision and reliability of the synchronous prediction of multi energy consumption indicators such as electricity and coal consumption are important for the production optimization of industrial processes (e.g., in the cement industry) due to the deficiency of the coupling relationship of the two indicators while forecasting separately. However, the time lags, coupling, and uncertainties of production variables lead to the difficulty of multi-indicator synchronous prediction. In this paper, a data driven forecast approach combining moving window and multi-channel convolutional neural networks (MWMC-CNN) was proposed to predict electricity and coal consumption synchronously, in which the moving window was designed to extract the time-varying delay feature of the time series data to overcome its impact on energy consumption prediction, and the multi-channel structure was designed to reduce the impact of the redundant parameters between weakly correlated variables of energy prediction. The experimental results implemented by the actual raw data of the cement plant demonstrate that the proposed MWMC-CNN structure has a better performance than without the combination structure of the moving window multi-channel with convolutional neural network.

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