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

• Journal of Korean Association for Spatial Structures
• /
• v.19 no.2
• /
• pp.101-108
• /
• 2019

In this paper, the characteristic of intrinsic mode function(IMF) and its orthogonalization of ensemble empirical mode decomposition(EEMD), which is often used in the analysis of the non-linear or non-stationary signal, has been studied. In the decomposition process, the orthogonal IMF of EEMD was obtained by applying the Gram-Schmidt(G-S) orthogonalization method, and was compared with the IMF of orthogonal EMD(OEMD). Two signals for comparison analysis are adopted as the analytical test function and El Centro seismic wave. These target signals were compared by calculating the index of orthogonality(IO) and the spectral energy of the IMF. As a result of the analysis, an IMF with a high IO was obtained by GSO method, and the orthogonal EEMD using white noise was decomposed into orthogonal IMF with energy closer to the original signal than conventional OEMD.

• Environmental and Resource Economics Review
• /
• v.24 no.1
• /
• pp.55-84
• /
• 2015

Korea is one of the few OECD countries having no binding Greenhouse gas (GHG) emissions reduction obligations under the Kyoto Protocol. Korea is going to enforce a powerful greenhouse gas emissions control to the industry from 2015. Current GHG reduction policies do not take into account the trade-off between economic growth and GHG mitigation, this approach will not be sustainable. Sectoral approach, considering industry by industry may be more eco-friend approach. This study verified the validity of the analysis results counted from whole procedure of energy input-output analysis and decomposition analysis to sector 'Organic basic chemical products' and 'Cement and concrete products'. Empirical test was performed using changes in energy consumption, production, process improvements and new facilities. Although the results showed unstable fluctuations from Divisia index decomposition analysis, it was verified that the entire procedure can provide a clue in understanding of the industry's energy and GHG footprint.

• Journal of Korean Society of Rural Planning
• /
• v.22 no.4
• /
• pp.25-36
• /
• 2016

The purpose of this study is to construct a quantitative evaluation method that can analyze the policy effectiveness with the construction of a implicit composite index incorporating spatial econometrics models. In order to propose a methodological framework for the program evaluation, this study conducts an empirical analysis with the application of the Comprehensive Rural Village Development Project (CRVDP) which explicitly claims to achieve comprehensive goal of community development. The present study pays particular attention to quantifying the composite evaluation index and drawing net effect through the application of a series of spatial econometrics models. The spatial unit of the analysis is drawn at Eup-Myeon level in rural areas in Korea, and the time horizon is in between 2005 and 2010. We utilize the Korean Agricultural Census data in 2005 and 2010. Three steps of methodological processes are needed to satisfy the objective of the present study. First, we apply factor analysis to construct the composite index that represents comprehensive settlement environment in rural area. The index should be matched with the main objective of the CRVDP. Second, we apply the derived index to a series of spatial econometrics model as dependent variable. Lastly, utilizing the estimated coefficients of the econometrics models, we apply decomposition technique to estimate CRVDP's net effect from both cross-sectional and longitudinal perspectives. We find that the results of the decomposition analysis by the execution of the CRVDP are positively associated with the explicit object of the project.

• Bulletin of the Korean Mathematical Society
• /
• v.55 no.4
• /
• pp.1221-1230
• /
• 2018

We derive a sharp decomposition formula for the state polytope of the Hilbert point and the Hilbert-Mumford index of reducible varieties by using the decomposition of characters and basic convex geometry. This proof captures the essence of the decomposition of the state polytopes in general, and considerably simplifies an earlier proof by the authors which uses a careful analysis of initial ideals of reducible varieties.

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

• Journal of Climate Change Research
• /
• v.9 no.4
• /
• pp.407-421
• /
• 2018

In this paper, I analyze the GHG (greenhouse gas) emission factor of the domestic railway transportation sector using the LMDI (Log Mean Divisia Index) methodology. These GHG factors are the emission factor effect, energy intensity effect, transportation intensity effect, and economic activity effect. The analysis period was from 2011 to 2016, and the analysis objects were an intercity railway, wide area railway, and urban railway. The results show that the GHG emission of railway transportation sector decreased during these 6 years. The factors decreasing the GHG emission are the emission factor effect, energy intensity effect, and transportation intensity effect, while the factor increasing the GHG emission is the economic activity effect.

• Journal of Service Research and Studies
• /
• v.6 no.1
• /
• pp.83-95
• /
• 2016

We examine the information transmission between the Service Industrial Production Index and the Service Industrial Wholesale and Retail Index, based on the returns data offered by the Korea Bank. The data includes daily return data from January 2000 to September 2015. Utilizing a dynamic analytical tool-the VAR model, Granger Causality test, Impulse Response Function and Variance Decomposition have been implemented. The results of the analysis are as follows. Firstly, results of Granger Causality test suggests the existence of mutual causality the Service Industrial Production Index precede and have explanatory power the Service Industrial Wholesale and Retail Index However the results also identified a greater causality and explanatory power of the Service Industrial Wholesale and Retail Index over the Service Industrial Production Index. Secondly, the results of impulse response function suggest that the Service Industrial Production Index show immediate response to the Service Industrial Wholesale and Retail Index and are influenced by till time 5 From time 2, the impact gradually disappears. Also the Service Industrial Wholesale and Retail Index show immediate response to the Service Industrial Production Index and are influenced by till time 2.5, the impact gradually disappears. Lastly, the variance decomposition analysis shows that the changes of return of Service Industrial Production Index are dependent on those of the Service Industrial Wholesale and Retail Index. This implies that returns on the Service Industrial Production Index have a significant influence over returns on the Service Industrial Wholesale and Retail Index. It contributes to the understanding of market price formation function through analysis of detached the Service Industrial Production Index and Service Industrial Wholesale and Retail Index. Finally, our results can be used as a guide by the Korea Bank and Republic of Korea and as well as Statistics Korea.

• Korean Journal of Organic Agriculture
• /
• v.24 no.1
• /
• pp.1-15
• /
• 2016

This paper aims to analyze inequality of maize self-sufficiency rate among countries in 1970-2011. Utilizing sub-group consistency of Generalized Entropy and Atkinson inequality index, the estimated maize self-sufficiency rate inequality is further decomposed into two steps' separate country groups. First, lower and upper income groups and then lower, lower middle, upper middle and high income groups are used based on the national classification of the world bank. It is inferred that 1980s' policy intervention and 1990s' Uruguay Round negotiations have different effect on the inequality among four different country groups.

• Environmental and Resource Economics Review
• /
• v.24 no.1
• /
• pp.189-224
• /
• 2015

To meet sectoral emission target by 2020 and prepare for the emission trading scheme from 2015, decomposition analysis of energy consumption and GHG emission is required by 18 subsectors in industry sector where emission targets are established. Log Mean Divisia Index decomposition method was used to analyze factors' effects on energy and emission in the industry sector and by 18 subsectors from 2004 to 2011. Industrial energy consumption was increased due to the production effect and energy intensity effect. However structure effect contributes to the decrease of energy consumption. In terms of emissions (including indirect emission due to electricity consumption) in the industry sector, only structure effect contributed to the emission reduction. Factors' effects by subsectors were different. Cement industry, which is included at Nonmetal shows different results from those of Nonmetal industry and machinery industry, which is a subsector of Fabricated Metal, was also similar. In this regard, we should not apply the policy implications from decomposition analysis of aggregated industry such as Nonmetal or Fabricated Metal to its subsectors uniformly and develop a differentiated policy for each subsector industry.