• 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.

• Journal of Labour Economics
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• v.43 no.2
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• pp.75-107
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• 2020

Using the data from 1980 to 2017, I show the long-term trends in the gender wage gap in Korea and analyze factors using decomposition method. It tended to decline until the 1990s, but gradually slowed after the 2000s. Gelbach(2016)'s decomposition method is used as an alternative rather than Blinder-Oaxaca decomposition. The results show that the proportion of explanation of traditional factors, such as age, education, firm size, industry and occupation, are continuously decreasing in explaining the gender wage gap. Expecially, the proportion of explanation of age and that of education have decreased, and that of industry tended to decrease in the 1990s but to increase after the 2000s.

• Korean Journal of Labor Studies
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• v.14 no.2
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• pp.59-93
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• 2008

본 논문은 한국고용정보원의 '대졸자 직업이동경로조사(2007)' 자료를 활용하여 청년 고학력자의 성별 노동시장 차별이 존재하는지를 확인하고자 하였다. 청년 고학력층은 경력단절, 육아와 가사부담에 따른 노동시장 차별을 비교적 덜 받을 것으로 예상된다는 점에서 이들 집단에서의 차별 존재는 최근 노동시장 문제를 파악하는 데 있어 매우 중요한 의미가 있다. 우리는 성별 노동시장 차별을 분석하기 위해서 차별에 관한 실증분석 방법으로 일반적으로 많이 사용되는 오하카 요인분해 모형을 활용하였다. 특히 고용차별을 확인하기 위해서 이항선택 모형에 적용한 요인분해 분석방법을 활용하였다. 전반적인 결론은 청년층 고학력자 여성들도 청년층 고학력자 남성에 비해 고용 및 임금차별을 경험한다는 것이다. 특히 본 연구에서는 성별 임금차별 뿐만 아니라 비정규고용 및 비공식고용과 같은 고용형태상의 차별도 확인할 수 있었다. 연령, 4년제졸 여부, 결혼여부가 성별 고용 및 임금격차를 초래하는 주요 요인으로 분석되었다.

• Environmental and Resource Economics Review
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• v.31 no.4
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• pp.825-848
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• 2022

This paper analyzed the factors for increasing energy consumption in the domestic manufacturing sector using the LMDI (Log mean division index) decomposition method for the period from 1999 to 2019. Among the LMDI decomposition analysis methods, both additive and multiplicative factor decomposition methods were used. in this analysis. According to the result of the analysis, the factor that increased energy consumption in the domestic manufacturing industry was the production effect, and the structure effect and intensity effect were found to be the factors that decreased energy consumption. In particular, the reduction of energy consumption due to the structure effect was greater than that of energy consumption effect due to the intensity effect. By period, it can be seen that energy consumption increased rapidly due to the production effect until 2011, but after that, the increase in energy consumption due to the production effect slowed down. On the other hand, after that, the energy reduction effect due to the structure effect and the intensity effect became prominent. In order to save energy in the manufacturing sector in the future, energy diagnosis and management through EMS (Energy management system) and FEMS (Factory energy management system) are more necessary. In addition, restructuring into a low-energy consumption industry seems more necessary.

• Proceedings of the Korea Technology Innovation Society Conference
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• 2017.05a
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• pp.3-11
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• 2017

한국의 지역별로 특화된 과학기술 연구개발과 투자가 지속적으로 강조되고 있다. 연구개발 특구로 지정도 확대되었다. 광역시도별 연구개발 투자가 확대되는 분위기에서 각 지역별 투자에 영향을 미치는 요인이 무엇인지 학술적 검토가 필요하다. 본 논문에서는 지수분해분석(Index Decomposition Analysis) 방법론을 적용하여 광역시도의 연구개발 투자 요인에 대한 분석을 시도하였다. 분석에 사용된 자료는 통계청에서 발행된 2010~2015년 동안 지역별 인구, 연구원수, 연구개발 투자비 등이다. 분석 결과 대전, 서울, 경기 지역의 연구개발 투자 증가가 두드러진 것으로 나타났으며 다른 지역은 상대적으로 낮은 것으로 나타났다.

• The Microorganisms and Industry
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• v.18 no.3
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• pp.10-22
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• 1992

퇴비화는 유기물이 생물의 작용에 의해 분해되면서 보다 안정화된 형태로 변형되어 가는 과정으로 여러가지 환경요인에 의해 영향을 받는다. 본 논문에서는 유기물의 퇴비화 과정에 영향을 주는 요인을 토양 생화학적 및 미생물학적 측면으로 분석하여 퇴비화 공정설계에 있어 분해원리의 이해에 도움을 주고자 하며, 퇴비화 후 최종적인 사용, 즉 농업적 이용 가능성에 대해서도 간략하게 기술하고자 한다.

• Environmental and Resource Economics Review
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• v.24 no.2
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• pp.411-433
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• 2015

This paper decomposed energy productivity changes across 14 Korean manufacturing industries into 5 components, technological catch-up(EC), technological progress(TC), and changes in labor-energy ratio(LC), capital-energy ratio(KC) and energy mix(EMC). Then we also figured out the possible relationship between energy productivity change and export growth rate across the industries. It is found that (1) technological progress, changes in capital-energy ratio and energy mix contribute to energy productivity growth in Korea during the sample period, (2) technological progress is the primary driving forces for energy productivity growth, (3) increase in export growth rate had a positive impact on energy productivity growth excepting a part of energy-intensive industries.

• Proceedings of the KSEEG Conference
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• 1999.04a
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• pp.181-183
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• 1999

• 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.23 no.2
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• pp.305-330
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• 2014

There has been a lot of studies to identify the driving forces of energy consumption. Many of them decomposed the final energy consumption into the intensity effect, structural effect, and production effect. Those approach, however, could not consider the transformation loss during the electric power generation. Therefore, in this study, we conducted a decomposition analysis on the primary energy use basis to reflect that transformation loss. Log mean Divisia index and refined Laspeyres methods were used for the index decomposition. As results, we could find out that the difference between two approaches were definite. The intensity effect in 2011 is -0.607 times against 1981 in the final energy case, but -0.236 times in the primary energy case. The structure effect in 2011 is 0.227 times against 1981 in the final energy case, but 0.434 times in the primary energy case. Therefore, an analysis on the primary energy basis is essential when conducting a decomposition analysis.