• Environmental Engineering Research
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• v.22 no.2
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• pp.193-202
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• 2017

The study estimated the relationship between carbon dioxide, crop and livestock production index in Ghana: Estimating the long-run elasticities and variance decomposition by employing a time series data spanning from 1960-2013 using both fit regression and ARDL models. There was evidence of a long-run equilibrium relationship between carbon dioxide emissions, crop production index and livestock production index. Evidence from the study shows that a 1% increase in crop production index will increase carbon dioxide emissions by 0.52%, while a 1% increase in livestock production index will increase carbon dioxide emissions by 0.81% in the long-run. There was evidence of a bidirectional causality between a crop production index and carbon dioxide emissions and a unidirectional causality exists from livestock production index to carbon dioxide emissions. Evidence from the variance decomposition shows that 37% of future fluctuations in carbon dioxide emissions are due to shocks in the crop production index while 18% of future fluctuations in carbon dioxide emissions are due to shocks in the livestock production index. Efforts towards reducing pre-production, production, transportation, processing and post-harvest losses are essential to reducing food wastage which affects Ghana's carbon footprint.

• East Asian Economic Review
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• v.28 no.1
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• pp.37-67
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• 2024

This paper analyses carbon emissions and value-added embodied in trade between two large developed countries, South Korea and the United States, during 2000-2014. Using multi-regional input-output (MRIO) tables, our analysis reveals that carbon emissions and value-added embodied in exports grew by 19% and 101% for South Korea but shrank by 43% and 7% for the United States. As a result, South Korea experienced a 40% increase in net carbon exports and 243% increase in net value-added exports. At the industry level, the primary drivers of changes in carbon exports were electricity and basic materials. The majority of industries in witnessed improvements in carbon intensities suggesting improved environmental efficiency. While both countries achieved a decoupling of carbon emissions from value-added exports, substantial year-to-year and sectoral variations were observed. Finally, structural decomposition analysis indicates that domestic supply-side factors played a role in decreasing emissions whereas foreign demand-side factors contributed to emissions increases. In line with the main findings, various implications for policy and future research are discussed.

• Environmental and Resource Economics Review
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• v.26 no.1
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• pp.1-35
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• 2017

This study investigates a decomposition analysis of the determinants of the reduced $CO_2$ emissions in seven OECD countries that implemented carbon taxes from 1995 to 2013. Recent studies on decomposition analysis of changes in $CO_2$ emissions focused on technology-based physical factors; however, this study analyzes the effects of a carbon tax as an economic factor. According to the results obtained by using the Log Mean Divisia Index, the energy intensity effect and the carbon tax effect contributed the most towards the reduction of total $CO_2$ emissions in the seven OECD countries. The results for each country show that the emissions decreased due to the energy intensity effect, while the effects of carbon tax and carbon tax revenues differed by policy and environment of the countries.

• Environmental and Resource Economics Review
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• v.15 no.1
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• pp.27-50
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• 2006

We estimate $CO_2$ emissions in Korea industry, 1990 and 2000 using a commodity- by-industry IO model ($CO_2$ hybrid IO mode]). Estimated $CO_2$ emissions in industries include both $CO_2$ emissions from direct and indirect consumption. The results show that total $CO_2$ emissions has increased by 51.6 million TC (Tonne of Carbon) from 64.4 million TC in 1990 to 115.5 million TC in 2000. By applying the structural decomposition analysis technique, we decompose change of $CO_2$ emissions in Korea industry between the period 1990~2000. In the decomposition, we figure out two contributing factors, changes in $CO_2$ coefficient and changes in final demand. The latter is further decomposed as growth effects and structural effects. We also estimated each factor's contribution to the changes in $CO_2$ emissions in industries between 1990~2000. The analysis can be used as a useful resource for policy makers in improving the effectiveness of $CO_2$ emissions mitigation policy.

• Environmental and Resource Economics Review
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• v.9 no.3
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• pp.489-513
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• 2000

This paper introduces a new method to estimate and decompose sources of carbon dioxide emissions using an input-output model with decomposition method free of residual usually associated with this kind of analysis. This method is different from others, using what we call 'mean rate-of-change index (MRCI)' for weights of the decomposed terms. Ang et al.(1998) asserted that logarithmic mean divisia index(LMDI) is superior to Laspeyres index(LI) or simple average divisia index(SADI) since it reduces residual to zero. We claim that our method is an improvement over the other methods because it enables residual free decomposition even when data contain negative values, the case which LMDI cannot handle. We demonstrate by way of showing some examples that our method is superior to LI, SADI(Proops, 1993 and Chung, 1998) or LMDI(Ang et al., 1998).

• Environmental and Resource Economics Review
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• v.20 no.2
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• pp.229-254
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• 2011

In this paper, we decomposed Greenhouse-Gas emissions of Korea's manufacturing industry using LMDI (Log Mean Divisia Index) method. Changes in $CO_2$ emissions from 1991 to 2007 studied in 5 different factors, industrial production (production effect), industry production mix (structure effect), sectoral energy intensity (intensity effect), sectoral energy mix (energy-mix effect), and $CO_2$ emission factors (emission-factor effect). By results, the structure effect and intensity effect has a role of reducing GHG emissions and The role of structure effect was bigger than intensity effect. The energy mix effect increased GHG emissions and emission-factor effect decreased GHG emissions. By time series analysis, IMF regime affected the GHG emission pattern. the structure effect and intensity effect in that regime was getting worse. After 2000, in the high oil price period, the structure effect and intensity effect is getting better.

• Environmental Engineering Research
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• v.22 no.1
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• pp.40-54
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• 2017

According to FAO, "agricultural sectors are particularly exposed to the effects of climate change and increases climate variability". As a result, the study makes an attempt to answer the question: Is there a causal effect between agricultural production and carbon dioxide emissions in Ghana? By employing a time series data spanning from 1960 to 2015 using the Autoregressive Distributed Lag method. There was evidence of a long-run equilibrium relationship running from copra production, corn production, green coffee production, milled rice production, millet production, palm kernel production and sorghum production to carbon dioxide emissions. The short-run equilibrium relationship shows that, a 1% increase in copra and green coffee production will increase carbon dioxide emissions by 0.22% and 0.03%, a 1% increase in millet and sorghum production will decrease carbon dioxide emissions by 0.13% and 0.11% in the short-run while a 31% of future fluctuations in carbon dioxide emissions are due to shocks in corn production. There was bidirectional causality between milled rice production and carbon dioxide emissions, millet production and carbon dioxide emissions and, sorghum production and carbon dioxide emissions; and a unidirectional causality running from corn production to carbon dioxide emissions and carbon dioxide emissions to palm kernel production.

• Environmental and Resource Economics Review
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• v.19 no.2
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• pp.243-282
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• 2010

In this paper, we analyze the components and trends of carbon emissions using the Logarithmic Mean Divisia Index decomposition method in Korean electricity industry during the period 1991~2007. In the demand side, carbon emissions are affected by electricity intensity and structural shift and especially electricity intensity is identified as the major factor which has lead carbon emissions decreasing. In the supply side, the result in variations of carbon emission for electric power generation depends on the influences of fossil fuel mix, fuel intensity, generation mix and so on. As a result fuel intensity is the most negative effect on both carbon emission intensity and the amount of carbon emission while the change of generation mix has a positive effect on increasing carbon emissions. And to conclude it needs to make the strategic policies to improve electricity intensity in the demand and to rise emission efficiency as well as to substitute thermal power generation in supply side.

• Environmental and Resource Economics Review
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• v.10 no.4
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• pp.569-589
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• 2001

We examine historical contributions of inter fuel substitution, changes in carbon efficiency and energy intensity, growth of economy and population to Korea's $CO_2$ emissions from 1970 to 1998 using the log mean weight Divisia index method. The study reveals that economic growth is the most significant factor to $CO_2$ emissions growth among the five factors. Changes in the fuel substitution and carbon coefficient are found negative contributors to $CO_2$ emissions growth. Energy intensity, which played dominant role in halting $CO_2$ emissions growth in the 1980s, began to play reversed role in the 1990s. When evaluated with the log mean Divisia index technique, deterioration of energy intensity in the 1990s is found worse and expected to contribute $CO_2$ emissions growth further.

• Journal of Climate Change Research
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• v.8 no.4
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• pp.357-367
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• 2017

Electricity generation in Korea mainly depends on thermal power and nuclear power. Especially the coal power has led to the increase in $CO_2$ emissions. This paper intends to analyze the current status of $CO_2$ emissions from electricity generation in Korea during the period 1990~2016, and apply the logarithmic mean Divisia index (LMDI) technique to find the nature of the factors influencing the changes in $CO_2$ emissions. The main results as follows: first, $CO_2$ emission from electricity generation has increased by $165.9MtCO_2$ during the period of analysis. Coal products is the main fuel type for thermal power generation, which accounts about 73% $CO_2$ emissions from electricity generation. Secondly, the increase of real GDP is the most important contributor to increase $CO_2$ emissions from electricity generation. The carbon intensity and the electricity intensity also affected the increase in $CO_2$ emission, but the energy intensity effect and the dependency of thermal power effect play the dominant role in decreasing $CO_2$ emissions.