scholarly journals A Cross-Sectoral Investigation of the Energy–Environment–Economy Causal Nexus in Pakistan: Policy Suggestions for Improved Energy Management

Energies ◽  
2021 ◽  
Vol 14 (17) ◽  
pp. 5495
Author(s):  
Rizwan Fazal ◽  
Syed Aziz Ur Rehman ◽  
Muhammad Ishaq Bhatti ◽  
Atiq Ur Rehman ◽  
Fariha Arooj ◽  
...  
Keyword(s):  
Economic Growth ◽  
Energy Consumption ◽  
Co2 Emissions ◽  
The Other ◽  
Economic Output ◽  
Industrial Sectors ◽  
Other Hand ◽  
Energy Environment ◽  
Pc Algorithm ◽  
Causal Nexus

This paper explored the energy–environment–economy (EEE) causal nexus of Pakistan, thereby reporting the causal determinants of the EEE nexus by employing the newly developed modified Peter and Clark (PC) algorithm. The modified PC algorithm was employed to investigate the causal ordering of energy consumption, CO2 emissions and economic growth across Pakistan’s domestic, industrial, transportation and agricultural sectors. An empirical comparison, i.e., following Monte Carlo simulation experiments demonstrates that the proposed modified PC algorithm is superior to the original PC proposition and can differentiate between true and spurious nexus causalities. Our results show that significant causality is running from energy consumption in industrial and agricultural sectors towards economic growth. There is no causal association between energy consumption and economic growth in the domestic and transportation sectors. On the other hand, causality runs from energy consumption in the transportation, domestic and industrial sectors towards CO2 emissions. It is concluded that energy consumption in industrial and agricultural sectors leads to economic growth alongside the associated CO2 emissions. On the other hand, the contribution of domestic and transportation sectors in economic growth is trivial with significant CO2 emissions. This paper provides novel empirical evidence of impacts of energy mismanagement at sectoral levels, economic output and environmental consequences; alongside policy recommendations for sustainable energy-based development on the national scale.

scholarly journals Economic Development, CO2 Emissions and Energy Use Nexus-Evidence from the Danube Region Countries

Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3165
Author(s):  
Eva Litavcová ◽  
Jana Chovancová
Keyword(s):  
Economic Growth ◽  
Energy Consumption ◽  
Co2 Emissions ◽  
Carbon Emissions ◽  
Bounds Testing ◽  
Mutual Cooperation ◽  
Long Run ◽  
Short Run ◽  
Danube Region ◽  
The Impact

The aim of this study is to examine the empirical cointegration, long-run and short-run dynamics and causal relationships between carbon emissions, energy consumption and economic growth in 14 Danube region countries over the period of 1990–2019. The autoregressive distributed lag (ARDL) bounds testing methodology was applied for each of the examined variables as a dependent variable. Limited by the length of the time series, we excluded two countries from the analysis and obtained valid results for the others for 26 of 36 ARDL models. The ARDL bounds reliably confirmed long-run cointegration between carbon emissions, energy consumption and economic growth in Austria, Czechia, Slovakia, and Slovenia. Economic growth and energy consumption have a significant impact on carbon emissions in the long-run in all of these four countries; in the short-run, the impact of economic growth is significant in Austria. Likewise, when examining cointegration between energy consumption, carbon emissions, and economic growth in the short-run, a significant contribution of CO2 emissions on energy consumptions for seven countries was found as a result of nine valid models. The results contribute to the information base essential for making responsible and informed decisions by policymakers and other stakeholders in individual countries. Moreover, they can serve as a platform for mutual cooperation and cohesion among countries in this region.

scholarly journals Does Green Energy Complement Economic Growth for Achieving Environmental Sustainability? Evidence from Saudi Arabia

2020 ◽  
Vol 13 (1) ◽  
pp. 180
Author(s):  
Montassar Kahia ◽  
Anis Omri ◽  
Bilel Jarraya
Keyword(s):  
Economic Growth ◽  
Saudi Arabia ◽  
Renewable Energy ◽  
Energy Consumption ◽  
Co2 Emissions ◽  
Environmental Sustainability ◽  
Least Square ◽  
Ekc Hypothesis ◽  
Renewable Energy Consumption ◽  
Ordinary Least Square

This study extends previous environmental sustainability literature by investigating the joint impact of economic growth and renewable energy on reducing CO2 emissions in Saudi Arabia over the period 1990–2016. Using the fully modified ordinary least-square (FMOLS) and dynamic ordinary least-square DOLS estimators, we find that economic growth increases CO2 emissions in all estimated models. Moreover, the validity of the environmental Kuznets curve (EKC) hypothesis is only supported for CO2 emissions from liquid fuel consumption. The invalidity of the EKC hypothesis in the most commonly used models implies that economic growth alone is not sufficient to enhance environmental quality. Renewable energy is found to have a weak influence on reducing the indicators of environmental degradation. We also find that the joint impact of renewable energy consumption and economic growth on the indicators of CO2 emissions is negative and insignificant for all the estimated models, meaning that the level of renewable energy consumption in Saudi Arabia is not sufficient to moderate the negative effect of economic growth on environmental quality. Implications for policy are also discussed.

scholarly journals Energy Consumption, Economic Growth, and CO2 Emissions in G20 Countries: Application of Adaptive Neuro-Fuzzy Inference System

Energies ◽  
2018 ◽  
Vol 11 (10) ◽  
pp. 2771 ◽  
Author(s):  
Abbas Mardani ◽  
Dalia Streimikiene ◽  
Mehrbakhsh Nilashi ◽  
Daniel Arias Aranda ◽  
Nanthakumar Loganathan ◽  
...  
Keyword(s):  
Economic Growth ◽  
Energy Consumption ◽  
Co2 Emissions ◽  
Fuzzy Inference System ◽  
Global Economy ◽  
Prediction Models ◽  
Fuzzy Inference ◽  
Anfis Model ◽  
Inference System ◽  
Neuro Fuzzy

Understanding the relationships among CO2 emissions, energy consumption, and economic growth helps nations to develop energy sources and formulate energy policies in order to enhance sustainable development. The present research is aimed at developing a novel efficient model for analyzing the relationships amongst the three aforementioned indicators in G20 countries using an adaptive neuro-fuzzy inference system (ANFIS) model in the period from 1962 to 2016. In this regard, the ANFIS model has been used with prediction models using real data to predict CO2 emissions based on two important input indicators, energy consumption and economic growth. This study made use of the fuzzy rules through ANFIS to generalize the relationships of the input and output indicators in order to make a prediction of CO2 emissions. The experimental findings on a real-world dataset of World Development Indicators (WDI) revealed that the proposed model efficiently predicted the CO2 emissions based on energy consumption and economic growth. The direction of the interrelationship is highly important from the economic and energy policy-making perspectives for this international forum, as G20 countries are primarily focused on the governance of the global economy.

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