Addressing the Drivers of Carbon Emissions Embodied in Indian Exports: An Index Decomposition Analysis

2019 ◽  
Vol 54 (4) ◽  
pp. 300-333 ◽  
Author(s):  
Suvajit Banerjee
Keyword(s):  
Scale Effect ◽  
Carbon Dioxide Emissions ◽  
Production Efficiency ◽  
Bilateral Trade ◽  
Export Performance ◽  
Decomposition Analysis ◽  
Index Decomposition Analysis ◽  
Index Decomposition ◽  
Emission Regulation ◽  
The Impact

This study identifies the determinants that have an observable impact over the change in carbon dioxide emissions embodied in the production of Indian exports by adopting an index decomposition analysis to address the contribution from four mutually non-exclusive factors which arise due to India’s increasing export performance during the 1995–2009 period on the change in total emissions embodied in exports. These four factors are scale effect, composition effect, emission regulation effect and production efficiency effect. The idea of bringing the last two effects is to capture the impact from technology factor due to international trade. This study found an increased emission embodiment in exports of 234.24 mega-tonnes by using input–output modelling with ‘emissions embodied in bilateral trade’ approach and then applies the Logarithmic Mean Divisia Index-I (LMDI-I)-based additive and multiplicative formulae following Ang and Zhang (2000) and Ang (2004) to conduct the decomposition exercise. This study finds the scale effect as the largest contributing factor increasing the emission levels by more than 184 per cent of the original increase, while the other three effects creating dampening impact over this scale-driven increase. Emission regulation effects created the maximum cleaning-up impact, especially during the 2002–2009 phase. JEL Codes: C67, F64, Q43, Q48, Q56

scholarly journals The “Eco-Effectiveness” of Agritourism Dynamics in Italy and Spain: A Tool for Evaluating Regional Sustainability

2020 ◽  
Vol 12 (17) ◽  
pp. 7080
Author(s):  
Angelo Belliggiano ◽  
Eugenio Cejudo Garcia ◽  
Marilena Labianca ◽  
Francisco Navarro Valverde ◽  
Stefano De Rubertis
Keyword(s):  
Rural Development ◽  
Circular Economy ◽  
Evolutionary Dynamics ◽  
Decomposition Analysis ◽  
New Approach ◽  
Sustainability Index ◽  
Index Decomposition Analysis ◽  
Index Decomposition ◽  
The Impact ◽  
Ecological Dimension

Rural tourism has commonly been identified as one of the main areas of application of the principles of sustainable tourism, but the literature has typically focused solely on the ecological dimension, particularly when referring to agritourism. This study presents a new approach to assessing the “eco-effectiveness” of the evolutionary dynamics of agritourism, as applied in a study of NUTS-2 regions in two European countries (Spain and Italy) that have implemented similar rural development strategies. To this end, a synthetic sustainability index was developed using the Index Decomposition Analysis (IDA) technique. The last period of the European Agricultural Fund for Rural Development (EAFRD) 2007–2013 was chosen for the study in order to analyze the outcomes of a programming cycle focusing on the diversification of agriculture through tourism. The results show that the sustainability of agritourism growth is not homogeneous and has specific features in different regions of the same country. In some cases, there were more similarities with regions from other countries. This tool could help evaluate the impact of agritourism and facilitate comparisons between different regions, in this way supporting the process of transition from a linear to a circular economy.

scholarly journals Analysing South Africa’s automotive energy consumption : application of index decomposition analysis

2021 ◽  
Author(s):  
◽  
Rofhiwa Tevin Machivha
Keyword(s):  
Energy Consumption ◽  
Decomposition Analysis ◽  
Structural Effect ◽  
Intensity Effect ◽  
Sectoral Shifts ◽  
Activity Effect ◽  
Index Decomposition Analysis ◽  
Index Decomposition ◽  
Industrial Energy ◽  
The Impact

This research focuses on applying the Index Decomposition Analysis (IDA) to South Africa’s automotive industry to decompose energy consumption and further make use of regression analysis to understand how it relates to the economy. South Africa has been going through an energy crisis, which has resulted in ongoing load shedding as a way to manage this crisis. Looking at South Africa’s energy generation, it can be noted that the entire country depends on Eskom as the main supplier and of electricity, but it is unable to keep pace with the demand. The results of the research show that there exists a nexus across all segments between energy consumption and GDP; furthermore, the decomposition results show that energy consumption in some years experienced a reduction. However, it can be seen that an increase in energy consumption year on year is predominant; this then suggests that the reductions experienced were the result of a special event; hence, it can be deduced that overall energy consumption has increased slightly. The increase is as a result of the activity effect which contributed the most towards this whilst the structural effect yielded a negligible contribution. Lastly, the intensity effect contributed to the reduction in energy consumption as a result of sectoral shifts; this reduction contributed towards keeping the overall increase in energy consumption low. This study aimed to outline the differences in energy consumed during the production of different vehicle classes, citing various factors responsible for the changes in energy consumption during vehicle production, raising awareness with manufacturers on the impact industrial energy consumption has on the national energy grid and on advising medium to large manufacturers to become suppliers.

scholarly journals Measuring energy efficiency - structural and index decomposition analysis

2018 ◽  
Vol 2 (4) ◽  
pp. 71
Author(s):  
Paulina Stachura
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Energy Use ◽  
Decomposition Analysis ◽  
Structural Decomposition Analysis ◽  
Energy Efficiency Improvement ◽  
Index Decomposition Analysis ◽  
Index Decomposition ◽  
Main Determinants ◽  
The Impact

Aim: The aim is to recognize the main determinants of the energy efficiency improvement in transport in Poland in the years 2000-2014 using structural and index decomposition analysis, and to identify areas where there is still potential for further reduction of energy consumption.Design / Research methods: Techniques used to analyse changes in energy use are: structural decomposition analysis and index decomposition analysis. Each of these two methods is characterized by distinctive, unique techniques and approaches, as they have developed quite independently. Index decomposition analysis measures the impact of energy efficiency gains on the level of energy consumption, at the most detailed sector disaggregation level allowed by the available data. Whereas structural decomposition analysis allows to analyse the impact of the external factors, such as technological, demand, and demographic effects, on the fluctuations of the total energy consumption. The similarities and differences between the two approaches are summarized and illustrated with a numerical example of Polish transport.Conclusions / findings: The article recognizes the main determinants of the energy efficiency improvement in transport sector in Poland in the years 2000-2014. In case of Poland ODEX shows an overall progress of energy efficiency in transport by 24.3%. Results obtained with decomposition analysis indicate large divergences in energy efficiency improvements between modes of transport and vehicle types and identify areas where there is still potential for further reduction of energy consumption. Results from decomposing structure of energy use, show activity effect to be main reason for energy use growth. The distribution of each mode in total traffic of passengers and goods changes toward less energy efficient modes. The only factor driving down the energy use is energy savings.Originality / value of the article: Using two methods of decomposition analysis and comparing obtained outcomes allows to get a broader view on energy use trends. Results presented in this article are a good starting point for further detailed analysis of changes in energy use of transport.

scholarly journals Index Decomposition Analysis on Factors Affecting Energy-Related Carbon Dioxide Emissions from Residential Consumption in Beijing

2017 ◽  
Vol 2017 ◽  
pp. 1-14 ◽  
Author(s):  
Fengyan Fan ◽  
Yalin Lei
Keyword(s):  
Rural Areas ◽  
Urban Areas ◽  
Carbon Dioxide Emissions ◽  
Decomposition Analysis ◽  
Impact Factors ◽  
Energy Structure ◽  
Factors Affecting ◽  
Index Decomposition ◽  
Urban And Rural Areas ◽  
The Impact

Beijing’s residential CO2emissions have become the main growth point of CO2emissions. However, the impact factors of the direct energy-related CO2emissions from residents in Beijing have not been previously evaluated. This paper accessed the key factors that affect the residents’ CO2emissions in Beijing from 1995 to 2015, using a newly built decomposition model with generalized Fisher index (GFI) and M-P model. The results were compared between urban and rural areas. Urban residential CO2emissions did not change during 1995–1999 but then grew rapidly after 1999, while rural residential CO2emissions fluctuated during the studied period. Increased per capita income is the most important pulling factor for the growth of residential CO2emissions, while energy consumption intensity is a decisive factor in inhibiting residential CO2emissions. Population size plays a pulling role in the growth of residential CO2emissions. Energy structure exerts a role in inhibiting residential CO2emissions, and its inhibition effect is stronger for urban residents. Average consumption propensity inhibits urban residential CO2emissions but has little effect on rural residential CO2emissions. The population migration from rural to urban areas in the urbanization process increases residential CO2emissions. To reduce residential CO2emissions, several recommendations have been proposed.

Decomposição do consumo de energia na indústria brasileira: efeitos do aumento da atividade entre 1970 - 2019

2021 ◽  
Vol 27 (1) ◽  
Author(s):  
Marlon Salazar
Keyword(s):  
Decomposition Analysis ◽  
Index Decomposition Analysis ◽  
Index Decomposition

A indústria é um dos setores da economia que mais consomem energia, sendo responsável por 32% do consumo final em 2019. Compreender como se comporta o consumo da indústria ao longo das décadas, decompondo a variação do consumo entre os efeitos atividade, estrutura e intensidade, através da decomposição de números índices, é de grande importância e é o objetivo principal deste trabalho. Este trabalho inova ao utilizar o método “Index Decomposition Analysis (IDA)” para os dados de consumo de energia industrial. Conclui-se que o efeito atividade é o principal responsável pelo aumento no consumo de energia, já que captura a participação do aumento da produção industrial sobre o consumo de energia. Por outro lado, o efeito intensidade cresce no período, o que indica que a indústria brasileira está se tornando menos eficiente no consumo de energia. Já o efeito estrutura contribui reduzindo o consumo no período estudado, o que indica que os setores energo intensivos perderam participação na produção industrial. Além disso, a partir da estimação da equação de demanda de energia utilizando como proxy do consumo o efeito atividade, constata-se que a elasticidade renda da demanda de energia foi de 1,57% no período, já que a elasticidade preço da demanda não é significante.

scholarly journals Driving Forces of Air Pollution in Ulaanbaatar City Between 2005 and 2015: An Index Decomposition Analysis

2020 ◽  
Vol 12 (8) ◽  
pp. 3185 ◽  
Author(s):  
Enkhjargal Enkhbat ◽  
Yong Geng ◽  
Xi Zhang ◽  
Huijuan Jiang ◽  
Jingyu Liu ◽  
...  
Keyword(s):  
Air Pollution ◽  
Driving Forces ◽  
Decomposition Analysis ◽  
Air Pollutant ◽  
Capital City ◽  
Energy Structure ◽  
Index Decomposition Analysis ◽  
Socioeconomic Drivers ◽  
Index Decomposition ◽  
Concentration Changes

Ulaanbaatar, the capital city of Mongolia, is facing serious air pollution challenges—especially during the cold and long winter months—mainly due to fossil fuel combustion. This study investigates the socioeconomic drivers of the sulfur dioxide (SO2), nitrogen dioxide (NO2), and particulate matter (PM2.5) concentration changes in Ulaanbaatar between 2005 and 2015 by applying the index decomposition analysis (IDA) method. Five socio-economic driving forces are considered in the decomposition analysis. All the driving forces contributed to more air pollution concentration changes in 2015 than in 2005, despite the decreasing trends of decomposition results for the period of 2010–2015. In general, economic growth, pollution intensity, and energy intensity significantly contributed to the changes of air pollutant concentrations, while energy structure and population growth had marginal effects. Finally, appropriate policy recommendations are proposed to the local government so that they can initiate feasible policies to effectively reduce air pollution, protect human health, and respond to climate change in Ulaanbaatar.

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