CO2 emissions, GDP and energy intensity: A multivariate cointegration and causality analysis for Greece, 1977–2007

2011 ◽  
Vol 88 (4) ◽  
pp. 1377-1385 ◽  
Author(s):  
Emmanouil Hatzigeorgiou ◽  
Heracles Polatidis ◽  
Dias Haralambopoulos
Keyword(s):  
Co2 Emissions ◽  
Energy Intensity ◽  
Causality Analysis ◽  
Multivariate Cointegration

scholarly journals MULTIVARIATE GRANGER CAUSALITY BETWEEN CO2 EMISSIONS, ENERGY INTENSITY AND ECONOMIC GROWTH IN PORTUGAL: EVIDENCE FROM COINTEGRATION AND CAUSALITY ANALYSIS

2015 ◽  
Vol 22 (1) ◽  
pp. 47-74 ◽  
Author(s):  
Muhammad SHAHBAZ ◽  
Farooq Ahmed JAM ◽  
Sadia BIBI ◽  
Nanthakumar LOGANATHAN
Keyword(s):  
Economic Growth ◽  
Granger Causality ◽  
Co2 Emissions ◽  
Financial Development ◽  
Unit Root ◽  
Energy Efficient ◽  
Energy Intensity ◽  
Causality Analysis ◽  
Long Run ◽  
Vecm Granger Causality

The present study aims to investigate the relationship between economic growth, energy intensity and CO2 emissions by incorporating financial development in CO2 emissions function using Portuguese annual data over the period of 1971–2011. The unit root problem of variables is examined by applying Zivot-Andrews unit root test and the ARDL bounds testing approach is for long run relationship. The direction of causal relationship between the series is examined by the VECM Granger causality approach and robustness of causality analysis is tested by innovative accounting approach (IAA). Our empirical evidence confirmed that the variables are cointegrated for long run relationship. The results exposed that economic growth and energy intensity increase CO2 emissions, while financial development condenses it. The VECM Granger causality analysis showed the feedback effect between energy intensity and CO2 emissions, while economic growth and financial development Granger cause CO2 emissions. The study suggests that environment degradation can be controlled by using energy efficient technologies. Financial development can also play its role in improving the environmental quality by encouraging investment in energy efficient technology to enhance domestic production and save the environment from degradation.

Fraud and Bank Performance in Nigeria – Var Granger Causality Analysis

e-Finanse ◽  
2020 ◽  
Vol 16 (1) ◽  
pp. 20-26
Author(s):  
Taiwo A. Muritala ◽  
Muftau A. Ijaiya ◽  
Olatanwa H. Afolabi ◽  
Abdulrasheed B. Yinus
Keyword(s):  
Control Systems ◽  
Granger Causality ◽  
Internal Control ◽  
Banking Sector ◽  
Bank Performance ◽  
Causality Analysis ◽  
Vector Autoregressive ◽  
Granger Causality Analysis ◽  
Long Run ◽  
Multivariate Cointegration

AbstractThis paper examines the causality between fraud and bank performance in Nigeria over the period 2000-2016 for quarterly financial data using Johansen’s Multivariate Cointegration Model and Vector Autoregressive (VAR) Granger Causality analysis. The results show a long-run relationship between the variables. Bank performance was found to be linked to Granger fraud variables and vice versa at 10% significant level. This study reveals that there was a direct causal relationship between bank performance and fraud because increase in fraudulent activities in the banking sector leads to reduction in bank performance. Hence, this study recommends that internal control systems of banks should be strengthened so as to detect and prevent fraud. In this way, bank assets would be protected.

scholarly journals Do Environmental Stringency Policies and Human Development Reduce CO2 Emissions? Evidence from G7 and BRICS Economies

2021 ◽  
Vol 18 (13) ◽  
pp. 6727
Author(s):  
Funda Hatice Sezgin ◽  
Yilmaz Bayar ◽  
Laura Herta ◽  
Marius Dan Gavriletea
Keyword(s):  
United States ◽  
United Kingdom ◽  
Human Development ◽  
Co2 Emissions ◽  
United States Of America ◽  
The United States ◽  
Cointegration Analysis ◽  
Causality Analysis ◽  
The United Kingdom ◽  
The Impact

This study explores the impact of environmental policies and human development on the CO2 emissions for the period of 1995–2015 in the Group of Seven and BRICS economies in the long run through panel cointegration and causality tests. The causality analysis revealed a bilateral causality between environmental stringency policies and CO2 emissions for Germany, Japan, the United Kingdom, and the United States of America, and a unilateral causality from CO2 emissions to the environmental stringency policies for Canada, China, and France. On the other hand, the analysis showed a bilateral causality between human development and CO2 emissions for Germany, Japan, the United Kingdom, and the United States of America, and unilateral causality from CO2 emissions to human development in Brazil, Canada, China, and France. Furthermore, the cointegration analysis indicated that both environmental stringency policies and human development had a decreasing impact on the CO2 emissions.

scholarly journals The Regional Inequity of CO2 Emissions per Capita in China

2017 ◽  
Vol 9 (7) ◽  
pp. 228 ◽  
Author(s):  
Ting Liu ◽  
Wenqing Pan
Keyword(s):  
Co2 Emissions ◽  
Emission Reduction ◽  
Co2 Emission ◽  
Energy Intensity ◽  
Industrial Structure ◽  
Theil Index ◽  
Energy Structure ◽  
Co2 Emission Reduction ◽  
Index Method ◽  
Per Capita

This paper combines Theil index method with factor decomposition technique to analyze China eight regions’ inequality of CO2 emissions per capita, and discuss energy structure, energy intensity, industrial structure, and per capita output’s impacts on inequality. This research shows that: (1) The trend of China regional carbon inequality is in the opposite direction to the per capita CO2 emission level. Namely, as the per capita CO2 emission levels rise, regional carbon inequality decreases, and vice versa. (2) Per capita output factor reduces regional carbon inequality, whereas energy structure factor and energy intensity factor increase the inequality. (3) More developed areas can reduce the carbon inequality by improving the energy structure, whereas the divergence of energy intensity in less developed areas has increased to expand the carbon inequity. Thus, when designing CO2 emission reduction targets, policy makers should consider regional differences in economic development level and energy efficiency, and refer to the main influencing factors. At the same time, upgrading industrial structure and upgrading energy technologies should be combined to meet the targets of economic growth and CO2 emission reduction.

scholarly journals Decomposition Analysis of CO2 Emissions for Turkey and Iran over 1990-2010

2014 ◽  
Author(s):  
Hasan Rüstemoğlu ◽  
Sevin Uğural
Keyword(s):  
Co2 Emissions ◽  
Scale Effect ◽  
Energy Intensity ◽  
Decomposition Analysis ◽  
Carbon Intensity ◽  
Composition Effect ◽  
Economic Sectors ◽  
Intensity Effect ◽  
The World ◽  
Laspeyres Index

There exists an important awareness for reduction of CO2 emissions to obtain a sustainable world. Together with this, there is a great deal of interest for decomposition analysis to see the accelerating and decelerating factors of CO2 emissions. The aim of this project is to decompose CO2 emissions in economic sectors for the two superpowers of Middle East, Iran and Turkey, over the time period between 1990 and 2010, for Turkey obtained a rapid growth performance in recent years and Iran which is the energy superpower of the world. Refined Laspeyres Index decomposition method and a consistent data gathered from the World Bank’s and UN’s databases have been used during the analysis. Five main sectors (agriculture, manufacturing, transportation, construction and other service sectors) and four main impacts (scale effect, composition effect, energy intensity effect and carbon intensity effect) have been considered to see the increasing and decreasing factors of CO2 emissions. Various interesting results are observed for both of the countries, for each of the economic sectors. Generally scale effect and energy intensity effect are the dominant impacts for all sectors of both countries. However composition effect and carbon intensity effect are also important contributors for economic activities of these two countries. Overall, our analysis showed that these two countries should pay attention for energy intensity and sustainable economic growth.

scholarly journals Spatio-Temporal Analysis of CO2 Emission Driving Force in Various Provinces in China Using the Extended STIRPAT-GWR Model

2021 ◽  
Author(s):  
Yulin Zhang
Keyword(s):  
Co2 Emissions ◽  
Co2 Emission ◽  
Energy Intensity ◽  
Industrial Structure ◽  
Temporal Analysis ◽  
Energy Structure ◽  
High Effect ◽  
Northern Regions ◽  
Spatio Temporal ◽  
Gwr Model

To fill the shortcomings of traditional research that ignores the driver’s own spatial characteristics and provide a theoretical support to formulate suitable emission reduction policies in different regions across China. In this pursuit, based on the panel data of provincial CO2 emission in 2007, 2012, and 2017, the present study employed the extended environmental impact assessment model (STIRPAT-GWR model) to study the effect of population, energy intensity, energy structure, urbanization and industrial structure on the CO2 emissions in 29 provinces across China. The empirical results show that the effect of drivers on the CO2 emissions exhibited significant variations among the different provinces. The effect of population in the southwest region was significantly lower than that of the central and eastern regions. Provinces with stronger energy intensity effects were concentrated in the central and western regions. The effect of energy structure in the eastern and northern regions was relatively strong, and gradually weakened towards the southeast region. The areas with high urbanization effect were concentrated in the central and the eastern regions. Furthermore, significant changes were observed in the high-effect regions of the industrial structure in 2017. The high-effect area showed a migration from the northwest and northeast regions in 2007 and 2012, respectively, to the southwest and southeast regions in 2017. Urbanization showed the strongest effect on the CO2 emissions, followed by population and energy intensity, and the weakest effect was exhibited by the energy and industrial structure. Thus, the effects of population and energy structure showed a downward trend, in contrary to the effect of urbanization on the CO2 emissions in China.

scholarly journals Using the LMDI Method to Analyze the Change in Greenhouse Gas Emissions in Turkish Sectors

2021 ◽  
Author(s):  
Abdulkadir BEKTAŞ
Keyword(s):  
Co2 Emissions ◽  
Heat Production ◽  
Economic Activity ◽  
Energy Intensity ◽  
Decomposition Analysis ◽  
Manufacturing Industries ◽  
Lmdi Method ◽  
Gaseous Fuels ◽  
Turkish Economy ◽  
Determining Factors

In this study, CO2 emissions of the Turkish economy are decomposed for the 1998–2017 period for four sectors; agriculture, forestry and fishery, manufacturing industries and construction, public electricity and heat production, transport, and residential. The analyses are conducted for five fuel types; liquid, solid, gaseous fuels, biomass, and other fuels. In decomposition analysis, Log Mean Divisia Index (LMDI) method is used. The analysis results point out that energy intensity is one of the determining factors behind the change in CO2 emissions, aside from economic activity. The fuel mix component, especially for the manufacturing industries and construction sector, lowers CO2 emissions during the crisis periods when the economic activity declines. Mainly, it is found that changes in total industrial activity and energy intensity are the primary factors determining the changes in CO2 emissions during the study period. Among GDP sectors, manufacturing industries and construction and public electricity and heat production are the two sectors that dominate the change in CO2 emissions. Additionally, the residential and transport sectors’ contributions have gained importance during recent years. Among the manufacturing industries and construction, the non-metallic minerals sector contributes to CO2 emissions, followed by the chemicals sector.

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