The Relationship Between Economic Growth, Energy Consumption, and CO2 Emissions

2020 ◽  
pp. 143-170
Author(s):  
Parisa Pakrooh ◽  
Esmaeil Pishbahar
Keyword(s):  
Economic Growth ◽  
Energy Consumption ◽  
Co2 Emissions ◽  
Growth Energy ◽  
The Relationship

Investigating the Causal Linkage Among Economic Growth, Energy Consumption and CO2 Emissions in Thailand: An Application of the Wavelet Coherence Approach

2020 ◽  
Vol 10 (1) ◽  
pp. 17-26 ◽  
Author(s):  
Tomiwa Sunday Adebayo ◽  
Gbenga Daniel Akinsola
Keyword(s):  
Economic Growth ◽  
Energy Consumption ◽  
Co2 Emissions ◽  
Time Series Data ◽  
Wavelet Coherence ◽  
Series Data ◽  
Energy Usage ◽  
Positive Correlation ◽  
Long Run ◽  
Growth Energy

The study aims to explore the causal linkage between CO2 emissions, economic growth and energy consumption in Thailand utilizing the wavelet coherence approach, conventional Granger and the Toda-Yamamoto causality techniques. In this study, In this study, time-series data spanning the period between 1971 and 2018 were used. No prior study has used the wavelet coherence approach to collect information on the association and causal interrelationship among these economic variables at different frequencies and timeframes in Thailand. The study objectives are structured to answer the following question: Does economic growth and energy consumption lead to CO2 emissions in Thailand?. The findings revealed that: (a) Changes in economic growth led to changes in CO2 emissions in Thailand at different frequencies (different scales) between 1971 and 2018. (b) A bidirectional causal relationship between CO2 emissions and energy consumption. (c) A positive correlation between CO2 emissions and energy usage in the short and long-run between 1971 and 2018. (d) A positive correlation between GDP growth and CO2 emissions in the short and long-run between 1971 and 2018. The study suggested that Thailand should initiate stronger policies towards enhancing the efficiency of energy and energy-usage programs to minimize unnecessary energy waste.

scholarly journals Analysis of Spatial Effects in the Relationship between CO2 Emissions and Renewable Energy Consumption in the Context of Economic Growth

Energies ◽  
2021 ◽  
Vol 14 (18) ◽  
pp. 5829
Author(s):  
Mateusz Jankiewicz ◽  
Elżbieta Szulc
Keyword(s):  
Economic Growth ◽  
Renewable Energy ◽  
Energy Consumption ◽  
Environmental Protection ◽  
Co2 Emissions ◽  
Indirect Effects ◽  
Renewable Energy Consumption ◽  
Spatial Spillovers ◽  
Spatio Temporal ◽  
The Relationship

The paper presents a spatial approach to the analysis of the relationship between air pollution, economic growth, and renewable energy consumption. The economic growth of every country is based on the energy consumption that leads to an increase in national productivity. Using renewable energy is very important for the environmental protection and security of the earth’s resources. Promoting environmentally friendly operations increases awareness of sustainable development, which is currently a major concern of state governments. In this study, we explored the influence of economic growth and the share of renewable energy out of total energy consumption on CO2 emissions. The study was based on the classical environmental Kuznets curve (EKC) and enriched with the spatial dependencies. In particular, we determined the spatial spillovers in the form of the indirect effects of changes in renewable energy consumption of a specific country on the CO2 emissions of neighboring countries. A neighborhood in this study was defined by ecological development similarity. The neighborhood matrix was constructed based on the values of the ecological footprint measure. We used the spatio-temporal Durbin model, with which the indirect effects were determined in relation to the spatially lagged renewable energy consumption. The results of our study also show the strength of the effects caused by imitating actions from the states with high levels of environmental protection. The study was conducted using data for 75 selected countries from the period of 2013–2019. Cumulative spatial and spatio-temporal effects allowed us to determine (1) the countries with the greatest impact on others and (2) the countries that follow the leading ones.

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