Factor Decomposition Analysis Research Articles

Factor Decomposition Analysis of Energy-Related CO2 Emissions in Tianjin, China

Tianjin is the largest coastal city in northern China with rapid economic development and urbanization. Energy-related CO2 emissions from Tianjin’s production and household sectors during 1995–2012 were calculated according to the default carbon-emission coefficients provided by the Intergovernmental Panel on Climate Change. We decomposed the changes in CO2 emissions resulting from 12 causal factors based on the method of Logarithmic Mean Divisia Index. The examined factors were divided into four types of effects: energy intensity effect, structure effect, activity intensity effect, scale effect and the various influencing factors imposed differential impacts on CO2 emissions. The decomposition outcomes indicate that per capita GDP and population scale are the dominant positive driving factors behind the growth in CO2 emissions for all sectors, while the energy intensity of the production sector is the main contributor to dampen the CO2 emissions increment, and the contributions from industry structure and energy structure need further enhancement. The analysis results reveal the reasons for CO2 emission changes in Tianjin and provide a solid basis upon which policy makers may propose emission reduction measures and approaches for the implementation of sustainable development strategies.

Substitutability and the Cost of Climate Mitigation Policy

We explore how and by how much the values of elasticities of substitution affect estimates of the cost of emissions reduction policies in computable general equilibrium (CGE) models. We use G-Cubed, an intertemporal CGE model, to carry out a sensitivity and factor decomposition analysis. The decomposition analysis determines the contributions of changes in average abatement costs and changes in baseline emissions to the change in total mitigation costs. The latter has not previously been considered. Average abatement cost rises non-linearly as elasticities are reduced. Changes in the substitution elasticities between capital, labor, energy, and materials have a greater impact on mitigation costs than do inter-fuel elasticities of substitution. The former have more effect on business as usual emissions and the latter on average abatement costs. As elasticities are reduced, business as usual emissions and GDP growth also decrease so that there is not much variation in the total costs of reaching a given target across the parameter space. Our results confirm that the cost of climate mitigation policy is at most a few percent of global GDP.

Factor decomposition analysis of sub-national CO2 emissions in China: A dynamic panel approach

The aim of this paper is to present new evidence of relationship between economic activities and environmental conditions, and accordingly to obtain emission-cutting focus in China. This study decomposes total CO2 emissions into six determinants derived from three net effects of Environmental Kuznets Curve (EKC): scale, technique, and composition. Meanwhile, in views of huge provincial-disparity in economic situation and environmental conditions, we investigate impact factors of CO2 emissions at sub-national level via generalized method of moment estimation. Test including panel unit root, panel cointegration, Sargan and residual auto-correlation is also performed to maintain strict structure and scientific estimation. Results show that CO2 emissions substantially increase over a decade with an upward annual growth rate and a high provincial disparity; sorted in descending order, previous CO2 emissions, coal share, economic growth, and industrial energy consumption are main determinants for accelerated CO2 emissions; EKC with an inverted-U shape relationship between environment quality and income is not verified. Accordingly, emission-reducing policies at sub-national level are concluded.

Linking Daly's Proposition to policymaking for sustainable development: indicators and pathways

The statement that in the full world, increasing the ultimate efficiency, expressed as service/throughput, is the necessary condition for humanity to achieve high levels of well-being within ecological limits is honoured as Daly's Proposition in this paper. The purpose of this paper is to make Daly's Proposition effective guidance for policymaking related to sustainable development. For this aim, this paper puts forward the indicator Ecological Well-being Performance, which is composed of the Human Development Index and the Ecological Footprint, to measure the ultimate efficiency. Furthermore, by means of matrix analysis and factor decomposition analysis, the respective pathways for countries at different stages of development to make the sustainable development transition were discussed. The G20 countries were taken as the cases to conduct the research. The empirical results show that improvements in well-being and increases in throughput level are not necessarily positively related. The relationship between the two depends on how countries control throughput levels and improve the Ecological Well-being Performance, which also explains different performances on the sustainable development transition. In a simple way, this contribution provides new methods and criteria to track and evaluate national performance on sustainable development by referring to Daly's original theories.

Continuous Function Modeling of Head-Related Impulse Response

A continuous function model is developed for efficient head-related impulse response (HRIR) representation. In this model, HRIR is modeled as the response of an IIR filter via common factor decomposition analysis, where HRIRs at the same azimuth but different elevations share the same IIR pole part and HRIRs at the same elevation but different azimuthes share the same IIR zero part. The pole and zero coefficients of the proposed common factor IIR (CF-IIR) filters are further modeled using sinusoidal functions of azimuth and elevation, respectively. A fast algorithm for evaluating sinusoidal function for efficient synthesis of virtual 3D sound is also developed.

A factor decomposition analysis of transportation energy consumption and related policy implications

This paper introduces a method of factor decomposition analysis for analyzing the importance of the factors that affect the volume of transportation energy consumption. In choosing the influencing factors from the many possibilities, the paper introduces an indicator analysis to evaluate and select the most important affecting factors. Based on the decomposition results, the paper helps interpret the underlying causes of transportation energy consumption. At the same time, the paper also suggests corresponding policy implications for the improvement of transportation energy efficiency.

Decomposition Analysis of Changes in Metropolitan Energy Consumption in China Based on the Logarithmic Mean Divisia Index

Abstract: The energy consumption of Chinas metropolitan areas has expanded from production areas to other areas such as the service area, and characteristics differ across small and medium-sized cities. Using the Logarithmic Mean Divisia Index (LMDI) decomposition method, we conducted a factor decomposition analysis on changes in energy consumption for 32 Chinese metropolises from 1995–2012 that had a resident population of at least 1 million people in 1995. On the basis of a comprehensive consideration of urban economic growth, population expansion and spatial expansion, energy consumption factors can be decomposed into five indicators: economic scale, energy consumption per unit of output value, energy consumption per capita, population density and energy space support coefficient. We valued the contribution of each factor to metropolises' energy consumption to determine generality and regional differences.

Substitutability and the Cost of Climate Mitigation Policy

We explore how and by how much assumptions about elasticities of substitution affect estimates of the cost of GHG emissions reduction policies in computable general equilibrium (CGE) models using G-Cubed, an intertemporal CGE model, to carry out a sensitivity and factor decomposition analysis. The results suggest that the average abatement cost rises non-linearly as elasticities are reduced. Substitution elasticities between capital, labor, energy and materials in production have a larger impact on mitigation costs than inter-fuel substitution does. There are notable differences in the effect of the elasticities on costs at the regional level due to interactions in international trade and capital flows in such a global model. Although the results in this study are derived from a particular model, the study, in a broader sense, suggests that there is a necessity for sensitivity analysis before making any conclusive policy recommendation using CGE models.

Comment on “Industry‐specific Real Effective Exchange Rates and Export Price Competitiveness: The Cases of Japan, China, and Korea”

Sato et al. (2013) represents a significant contribution to the literature. The novelty of their paper lies in the construction of a new dataset on industry-specific real effective exchange rates (REER) on a monthly basis from January 2005 to the present. The authors have convincingly demonstrated that REER differs not only between countries, but also across industries, a finding that would have slipped through the net of aggregate data analysis. The authors have used the industry-wise producer price index (PPI), instead of consumer price index (CPI), not only because the latter includes nontradables, but also because the former tends to vary across industries, reflecting interindustry differences in costs arising from differences in their exposure to exchange rate changes. In this context, industries with large import content are more sensitive to exchange rate changes than those with a large domestic content. It, thus, makes considerable sense to use the industry breakdown PPI data. However, exchange rate changes, in purchasing power parity (PPP) terms, can only be explained by the inflation differential. According to PPP, a currency with a relatively lower inflation rate would appreciate vis-a-vis currency with a higher inflation rate. Seen in these terms, one might still argue that CPI is more relevant for explaining exchange rate appreciations and depreciations, be they in nominal or real terms. The spotlight on the electric machinery industry is revealing. The results show that the Japanese electric machinery REER exhibits the largest depreciation among Japanese industries. This finding suggests that Japanese electric machinery should be enjoying substantial export price competitiveness. On the contrary, the Japanese electric machinery firms are suffering from worsening business performance and tougher competition in the export market. The explanation given by the authors is that Japan’s competitors in the electric machinery industry, especially the Korean firms, enjoy a much larger REER depreciation, and hence stronger export price competitiveness. This is further supported by the results of a factor decomposition analysis that attributes the Korean electric machinery export price competitiveness to a significant drop in domestic producer prices in Korea during the won appreciation period.

Analysis of virtual water consumption in China: using factor decomposition analysis based on a weighted average decomposition model

AbstractExploring the cause‐and‐effect relationship between economic sectors and water resources is important to China. This study implemented a factor decomposition analysis by weighted average decomposition (WAD) model on the changes of Chinese virtual water (VW) consumption between 2002 and 2007, which includes both direct water consumption (consumed to produce final products) and indirect water consumption (consumed to produce intermediate products). The change in VW consumption is decomposed into three determinant factors: technological effect, economic structural effect and the products' scale effect. The results show that the volume of VW consumption in China has decreased from 5.92 × 1011 m3 in 2002 to 5.17 × 1011 m3 in 2007, which is mainly because of the technological effect (−5.48 × 1011 m3). The increase in net VW exports is mainly due to the economic structure effect (6.19 × 109 m3) and the fast growth of exports (3.49 × 1010 m3).

Estimation of energy-related carbon emissions in Beijing and factor decomposition analysis

We calculated energy-related carbon emissions from Beijing's production and household sectors in 1995, 2000, 2005, and 2009 based on the default carbon-emission coefficients provided by the Intergovernmental Panel on Climate Change (IPCC). Taking 1995–2000, 2000–2005, and 2005–2009 as the study periods, we decomposed the effects of changes in carbon emissions resulting from eight causal factors using the logarithmic mean divisia index method: economic activity and population size, which reflect the change in socioeconomic activity; energy intensity and energy consumption per capita, which reflect the change in the intensity of energy use; and economic structure, the urban and rural population distribution structure, and the energy mix of the production and household sectors, which reflect structural changes. We found that in all three study periods, the changes in economic activity, population size, and energy consumption per capita stimulated emissions, whereas the changes in energy intensity, the urban and rural population distribution structure, and the energy mix of the production and household sectors decreased emissions. In contrast, changes in the economic structure decreased emissions in the first and third periods, and increased emissions in the second period. Our results clearly indicate that under current practices, carbon emissions will increase as a result of rapid growth of the economy, the population, and the energy consumption per capita. In the future, the main routes to reduce carbon emissions will be to adjust the economic structure and energy mix, and to reduce the energy intensity of each sector.

Supramolecular Interaction of Coumarin 1 Dye with Cucurbit[7]uril as Host: Combined Experimental and Theoretical Study

Molecules of the coumarin family have fluorescence characteristics that are highly sensitive to their environment, and thus, they have been used as fluorescent sensors in chemical and biological systems. However, the very poor fluorescence yield of most coumarin dyes in aqueous media limits their applications. We have adopted a supramolecular strategy to improve the fluorescence intensity of coumarin dye through its interaction with the relatively new host cucurbit[7]uril (CB[7]). The virtually nonfluorescent coumarin 1 (Φ(f) = 0.04) was converted into a highly fluorescent (Φ(f) = 0.52) entity in water upon addition of the nonfluorescent host CB[7]. Various spectroscopy techniques, namely, UV-vis absorption and steady-state and time-resolved fluorescence spectroscopies, established the formation of a strong 1:1 dye-CB[7] inclusion complex with a high binding constant of (1.2 ± 0.1) × 10(5) M(-1) for the dye. The stable inclusion complex of the neutral molecule was supported by density-functional-theory- (DFT-) based quantum chemical calculations. Energy decomposition analysis of various interaction factors in the host-guest complex revealed that key components providing stability to the complex were electrostatic, polarization, and charge-transfer energies. These new results on the formation of a strong inclusion complex of the versatile fluorophore coumarin 1 with the nontoxic host CB[7] could lead to the design of efficient molecular-scale biological probes, sensors, and photostable aqueous UV dye lasers.

An Estimation and Factor Decomposition Analysis of Energy-related Carbon Emissions in Beijing

Abstract We calculated energy-related carbon emissions from Beijing's production and household sectors in 1995, 2000, 2005, and 2009 based on the default carbon-emission coefficients provided by the Intergovernmental Panel on Climate Change (IPCC). Taking 1995-2000, 2000-2005, and 2005-2009 as the study periods, we decomposed the effects of changes in carbon emissions resulting from 8 causal factors using the method of the Logarithmic Mean Divisia Index (LMDI). These causal factors include: economic activity and population size which reflect the effect of activity change; energy intensity and energy consumption per capita which reflect the effect of intensity change; economic structure, urban and rural population distribution structure, and energy mix of production and household sectors which reflect the effect of structural change. Our results can reflect the reason of carbon emissions changes and provide a solid basis for policy makers to propose emission reduction measures and approaches.

The impact of household capital income on income inequality—a factor decomposition analysis for the UK, Germany and the USA

This paper analyses the contribution of capital income to income inequality in a cross-national comparison. Using micro-data from the Cross-National Equivalent File (CNEF) for three prominent panel studies, namely the BHPS for the UK, the SOEP for West Germany, and the PSID for the USA, we use the factor decomposition method described by Shorrocks (Econometrica 50:193–211, 1982). The factor decomposition of disposable income into single income components shows that capital income is exceedingly volatile and that its share in disposable income has risen recent years. Moreover, capital income makes a disproportionately high contribution to overall inequality in relation to its share in disposable income. This applies to Germany and the USA in particular. Thus capital income accounts for a large part of disparity in all three countries.

The Impact of Household Capital Income on Income Inequality - A Factor Decomposition Analysis for Great Britain, Germany and the USA

This paper analyses the contribution of capital income to income inequality in a cross-national comparison. Using micro-data from the Cross-National Equivalent File (CNEF) for three prominent panel studies, namely the BHPS for Great Britain, the SOEP for West Germany, and the PSID for the USA, a factor decomposition method described by Shorrocks (1982) is applied. The factor decomposition of disposable income into single income components shows that capital income is exceedingly volatile and its share in disposable income has risen in recent years. Moreover, capital income makes a disproportionately high contribution to overall inequality in relation to its share in disposable income. This applies to Germany and the USA in particular. Thus capital income accounts for a large part of disparity in all three countries.

The Impact of Household Capital Income on Income Inequality: A Factor Decomposition Analysis for Great Britain, Germany and the Usa

This paper analyses the contribution of capital income to income inequality in a cross-national comparison. Using micro-data from the Cross-National Equivalent File (CNEF) for three prominent panel studies, namely the BHPS for Great Britain, the SOEP for West Germany, and the PSID for the USA, a factor decomposition method described by Shorrocks (1982) is applied. The factor decomposition of disposable income into single income components shows that capital income is exceedingly volatile and its share in disposable income has risen in recent years. Moreover, capital income makes a disproportionately high contribution to overall inequality in relation to its share in disposable income. This applies to Germany and the USA in particular. Thus capital income accounts for a large part of disparity in all three countries.

An extended method for key factors in reducing CO 2 emissions

Understanding the key factors in regard to CO 2 emissions is beneficial in providing a basis for reducing CO 2 emissions in the future. Generally speaking, from related studies in the literature on the key factors influencing CO 2 emissions, three types of effect can be inferred, namely, the output effect, structural effect and the intensity effect. If we are able to engage in analysis using an objective, quantitative analytical approach, namely, the factor decomposition analysis approach, this will serve as valuable reference to policy-makers who are seeking to implement reductions in CO 2 emissions. In this paper, we use the Divisia logarithmic average analytical method referred to by Ang and Choi [B.W. Ang, K.H. Choi, Decomposition of aggregate energy and gas emission intensities for industry: a refined Divisia index method, The Energy Journal 18 (3) (1997) 59–73] as the basic analytical framework. While most studies only focused on between three and five variables when performing the decomposition, in this study we first of all decompose the CO 2 emission factors into five factors, namely, population, economic growth, the contamination coefficient, energy intensity and the industrial structure effect. Moreover, in this study we examine in detail the most important factor to influence CO 2 emissions (i.e., the output effect), which we partially decompose (using an expanded model), so that our decomposition of the CO 2 emission factors can be more comprehensive. In this way, we can provide policy-makers with more effective and in-depth evidence that can serve as valuable reference for them.

Economic analysis of water resources in Japan: using factor decomposition analysis based on input-output tables

This article explores the cause-and-effect relationship between the exports of manufactured goods and water resources (virtual water). Little is known about virtual water flows in relation to Japan’s exports of manufactured goods. The research is based on the Japanese input-output tables and factor decomposition analysis (1980–2000). Virtual water exports include both “direct” water exports (the water utilized to manufacture final goods) and “indirect” water exports (the water required to produce intermediate goods). In the analysis, the change in virtual water exports is decomposed into three determinant factors: the direct water coefficient change, indirect water coefficient change, and export volume change. The findings imply that the export volume change was the most influential factor in determining the total volume of Japanese virtual water exports in the early 1980s; however, the volume of indirect water change exerts a stronger influence on the massive virtual water exports now and is greatly affected by subsidiaries. Manufacturers depend on the supply of water from developing countries to enhance their competitive strengths. Thus, the article suggests possible changes in virtual water trade flows between Japan and other countries.

How Japan–US Economic Interdependence Changed from 1985 to 1990: Some Findings from Price-adjusted MITI Intercountry Input–Output Tables

This paper consists of two parts. First, constant-price Japan–US intercountry input–output (IO) tables are compiled, based on Japan–US IO tables of the Ministry of International Trade and Industry (MITI) for 1985 and 1990, and the relative producer prices of both countries, which are estimated by the ‘peeling off’ method from OECD purchasing power parity data. Second, a factor decomposition analysis is carried out to show changes in Japan–US economic interdependence between 1985 and 1990. The Leontief inverse matrices of intercountry IO tables are decomposed into three matrices, which reflect domestic repercussion effects, spillover effects to the other country and feedback effects of own final demand from the other country. Then, a traditional decomposition analysis of changes in production for both countries is applied to see how both countries' economic interdependence changed. It is found that Japan–US economic interdependence moved from a pattern of Japan's dependence on the US to an almost equally interdependent pattern, although the degree of dependence was still higher in Japan in 1990. At the same time, there are significant industrial structural changes in the relationship between both countries, as a result of the significant appreciation of the yen relative to the dollar from 1985 to 1990.

The Impact of Technical Change, Scale Effects, and Forward Ordering on U.S. Fiber Demands

AbstractThis paper estimates a complete system of input cost shares in U.S. textile production, using time‐series data and a linear logit specification incorporating the impact of technical change and scale effects on derived demands for natural and manmade fibers. The specification accounts for forward ordering dynamics in the textile industry. Technical change has decreased natural fiber use in U.S. textile mills in favor of manmade fibers. Decomposition analysis of economic factors affecting long‐run use of natural versus manmade fiber indicates that nonprice factors account for 70% of the decline in long‐run natural fiber use.