Variance analysis of global CO2 emission – A management accounting approach for decomposition study

Pani, Ratnakar; Mukhopadhyay, Ujjaini

doi:10.1016/j.energy.2010.10.015

Cited by 17 publications

(15 citation statements)

References 20 publications

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“…The word 'variance' used in the study is given by Pani and Mukhopadhyay [22,23] who first introduced this method in the emission studies. Variance analysis is the process of analyzing variance (the change) by subdividing the total variance (total change) in such a way that management can assign responsibility for off-standard performance.…”

Section: Variance Analysismentioning

confidence: 99%

“…On the other hand, the main dominant factors of the reduction of the emission are the intensity effects which comprise both end-use energy intensity and fuel conversion intensity. However, LMDI method has some drawbacks in terms of its incapability of handling negative and zero values in environmental data set (Pani and Mukhopadhyay [22,23], Wood and Lenzen [33]). Therefore to eliminate the problem, Chontanawat [34] adopted the IPAT method combined with variance analysis, based on Pani and Mukhopadhyay [22,23] to investigate the driving forces of CO 2 emissions for ASEAN (not specific to individual countries) for the longer period 1971-2013.…”

Section: Introductionmentioning

confidence: 99%

“…However, LMDI method has some drawbacks in terms of its incapability of handling negative and zero values in environmental data set (Pani and Mukhopadhyay [22,23], Wood and Lenzen [33]). Therefore to eliminate the problem, Chontanawat [34] adopted the IPAT method combined with variance analysis, based on Pani and Mukhopadhyay [22,23] to investigate the driving forces of CO 2 emissions for ASEAN (not specific to individual countries) for the longer period 1971-2013. It was found that population growth and increased income per capita have the largest contribution to emission growth; fossil fuels increasingly become the dominant fuel; energy efficiency and carbon intensity (emission factor) are the factors that reduced emissions.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Driving Forces of Energy-Related CO2 Emissions Based on Expanded IPAT Decomposition Analysis: Evidence from ASEAN and Four Selected Countries

Chontanawat

2019

Energies

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ASEAN is a dynamic and diverse region which has experienced rapid urbanization and population growth. Their energy demand grew by 60% in the last 15 years. In 2013, about 3.6% of global greenhouse-gas emissions was emitted from this region and the share is expected to rise substantially. Hence, a better understanding of driving forces of the changes in CO2 emissions is important to tackle global climate change and develop appropriate policies. Using IPAT combined with variance analysis, this study aims to identify the main driving factors of CO2 emissions for ASEAN and four selected countries (Indonesia, Malaysia, Philippines and Thailand) during 1971–2013. The results show that population growth and economic growth were the main driving factors for increasing CO2 emissions for most of the countries. Fossil fuels play an important role in increasing CO2 emissions, however the growth in emissions was compensated by improved energy efficiency and carbon intensity of fossil energy. The results imply that to decouple energy use from high levels of emissions is important. Proper energy management through fuel substitution and decreasing emission intensity through technological upgrades have considerable potential to cut emissions.

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Section: Variance Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Driving Forces of Energy-Related CO2 Emissions Based on Expanded IPAT Decomposition Analysis: Evidence from ASEAN and Four Selected Countries

Chontanawat

2019

Energies

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“…Thus, it is recommended to develop renewable energy. Ratnakar Pani and Ujjaini Mukhopadhyay [6] , by using the method of management accounting and variance decomposition, research the global carbon emissions. The results reveal that compared to population, GDP growth has greater impact on carbon emissions, and the growing carbon emissions is closely related to the lack of energy management.…”

Section: Literature Reviewmentioning

confidence: 99%

Analysis on China’s Recent Situation and Measurement of Energy Conservation and Emissions Reduction

Wang¹

2018

dtetr

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Abstract. The purpose of this study is to examine China's approach to achieve energy conservation and emissions reduction. A questionnaire with rated response is designed to investigate people's understanding and attitudes to energy conservation and emissions reduction. As climate change is more relevant to the next generation, two groups (the married and the unmarried) are compared in the survey, the findings indicate that the married couples pay more attention to the issue of carbon emissions. The author applies Likert scaling method to analyze the data. Results indicate that emotional attachment, budget constrain, loss averse and imposed risks can be used to explain why WTAC is much larger than WTP. China's carbon emissions have accounted for 24% of the world's carbon emissions since 2011, and that brings China great pressure to reduce emissions. Direct regulation, marked-based instruments such as taxes and subsidies, and low carbon economic development especially energy efficiency improvement as well as clean energy development are recommended to solve the issue of carbon emissions.

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“…The consumer lifestyle approach of different regions and income levels was used by [8] to analyze and explain the impact of carbon dioxide emissions and energy consumption by urban and rural households in China. An alternative decomposition method based on variance analysis was recommended by [9] to examine the relationship between energy-related CO 2 emission and its main factors for 156 sample countries. Reference [10] proposed a dynamic panel data model to examine the determinants of carbon dioxide emissions for a global panel involving 69 countries.…”

Section: Literature Reviewmentioning

confidence: 99%

An empirical study on CO<inf>2</inf> emissions in ASEAN countries

Hui

Rahman

Labadin

2012

2012 International Conference on Statistics in Science, Business and Engineering (ICSSBE)

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Estimates of carbon dioxide (CO 2 ) emissions are currently an important issue due to the enhanced greenhouse effect which leads to the phenomenon called global warming. This study focuses on ASEAN countries and applies regression analysis to examine interrelationship among the determinants of CO 2 emissions. Stepwise multiple regression models are developed using seven indicators and the generated interaction variables are also included in the entire possible models. There are four main phases involved, namely data collection and preparation phase, model identification and estimation phase, model refinement and selection phase, and model validation phase. These four main phases are jointed and summarized as an algorithm of regression model-building. By taking the best model into account, it is found that energy consumption, GDP, population and income group have statistically significant effects on CO 2 emissions. From the findings, there exists interaction effects in the best model obtained.

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Variance analysis of global CO2 emission – A management accounting approach for decomposition study

Cited by 17 publications

References 20 publications

Driving Forces of Energy-Related CO2 Emissions Based on Expanded IPAT Decomposition Analysis: Evidence from ASEAN and Four Selected Countries

Driving Forces of Energy-Related CO2 Emissions Based on Expanded IPAT Decomposition Analysis: Evidence from ASEAN and Four Selected Countries

Analysis on China’s Recent Situation and Measurement of Energy Conservation and Emissions Reduction

An empirical study on CO<inf>2</inf> emissions in ASEAN countries

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