Index Decomposition Approach Research Articles

Decoupling Economic Growth from Carbon Emissions in the Yangtze River Economic Belt of China: From the Coordinated Regional Development Perspective

Decoupling economic growth from carbon emissions is crucial for combating the climate crisis and promoting green development. However, a uniform approach to climate mitigation exacerbates regional disharmony. As a microcosm of China’s regional heterogeneity, the Yangtze River Economic Belt (YREB) is helpful in exploring regional collaborative climate governance. This paper uses the Thiel index, the Tapio decoupling model, and the Logarithmic Mean Divisia Index (LMDI) decomposition approach to explore the decoupling of economic growth from carbon emissions in YREB from 2005 to 2019. Results indicate that the carbon intensity difference is mainly from the difference within middle-rising provinces (MRP) and western less-developed provinces (WLP). YREB exhibits strong decoupling overall, but it is not sustained. The economic growth effect significantly promotes carbon emissions, which is more prominent in MRP. The energy intensity effect plays a vital role in restraining carbon emissions. The emission factor effect signals an improved energy structure in WLP. Regional coordination is needed to achieve green development; thus, provinces should set differentiated carbon emission reduction targets, and more potent tools are recommended in major carbon emitters.

Monetary policy spillovers among five systemic economies: Evidence from the time and frequency domains

Using the spillover index and frequency decomposition approach, this study explores the direction and magnitude of cross-border monetary policy spillovers among five systemic economies (S5): the United States, the Euro area, Japan, the United Kingdom, and China. The results suggest that China is the largest receiver and delivers the least to the other countries. Further, the findings reveal that massive monetary easing led by unconventional monetary policy implemented at home can transmit spillovers abroad. Notably, the overall spillover index peaks during a crisis. Moreover, both the static and dynamic frequency results show that short-term effects dominate spillovers. These findings suggest that both policymakers and investors should prevent foreign beggar-thy-neighbour monetary policies.

The synergy between temporal and spatial effects of human activities on CO2 emissions in Chinese cities

Based on the IPAT (I = human impact, P = population, A = affluence, and T = technology) framework, we used the temporal and spatial Logarithmic Mean Divisia Index decomposition approach to investigate whether the temporal and spatial impacts of human activities on carbon emissions are synergistic in 330 prefecture-level cities in China from 2003 to 2017. The results showed that carbon emissions in Chinese cities increased to different degrees during the study period, and a spatial distribution pattern could be recognized, with high levels in the East and South, and low levels in the West and North. Carbon emissions in cities in North China and in the eastern coastal areas displayed a cluster pattern higher than the national average level, although in most cities were lower than the national average. With respect to temporal effects, we found that although the decrease in carbon intensity played an important role in reducing carbon emissions in cities, it was not sufficient to offset the incremental gains associated with economic growth. The effect of population change was not apparent. With respect to spatial effects, we found that the effect of carbon intensity in most cities enhanced the difference with the national average carbon emission, whereas the effect of economic development reduced it. The effect of population size on spatial differences in carbon emission was bound by the Heihe–Tengchong line, forming a distribution pattern in which the difference in emissions was enhanced in the Southeast and reduced in the Northwest. The temporal and spatial impacts of human activities on carbon emissions in most cities were not synergistic. These findings can provide a reference for formulating differentiated carbon emission reduction policies among cities.

"Decomposition Analysis of Dynamic Changes in Aggregate Crop Revenue in Kymore Plateau Agro-climatic Zone of Madhya Pradesh"

"The study attempted to analyze the dynamic changes in the value of aggregate crop revenue by using Logarithmic Mean Divisia Index (LMDI) decomposition approach. Five districts of the Kymore plateau agro-climatic zone of Madhya Pradesh, i.e. Jabalpur, Katni, Panna, Satna & Sidhi were selected in the study for the period from 2007-08 to 2016-17. In the study the aggregate crop revenue was decomposed into the area, price, cropping pattern and yield effect. The results revealed more inclination of the farmers in Jabalpur district towards cereal crops, while in Panna and Katni districts; more inclination was observed towards oilseeds. Relative change for almost all the crops was negative in the Sidhi district except for wheat, gram and tur. The study revealed that in the agro-climatic zone, during the study period yield effect was the predominant factor, followed by price effect except for Jabalpur district, where price effect was dominant, followed by yield effect. Amid the different effects, cropping pattern effect had the most minuscule contribution in the agro-climatic zone."

Population density regulation may mitigate the imbalance between anthropogenic carbon emissions and vegetation carbon sequestration

The growing imbalance between anthropogenic carbon emissions and vegetation carbon sequestration is impeding cities’ sustainability. However, previous research has not reached a consensus on whether population density regulation can mitigate this growing imbalance. In this study, we first used the carbon footprint pressure (CFP) indicator to examine the temporal and spatial characteristics of the imbalance in 370 Chinese cities over the last 20 years. Second, we demonstrated the favorable but limited effect of existing technology on CFP mitigation using the IPAT equation, the Logarithmic Mean Divisia Index decomposition approach, and the Kaya identity. Further, we emphasized the dominant effect of the population on CFP in urban agglomerations and provincial capital cities through Maxwell's triangle. Finally, using a built panel data model, we identified an inverted U-curve relationship between CFP and population density at the middle and low quartiles, whereas population clustering promoted CFP mitigation at the upper quartiles. Given the limited effectiveness of current climate actions, as well as the coexistence of urban diseases and unoccupied buildings, we provided differentiated policy implications in city-scale for population density regulation. This study provides some inspiration for authorities to formulate city-scale population policies to mitigate climate change and achieve sustainable development.

Further mitigating carbon footprint pressure in urban agglomeration by enhancing the spatial clustering

The increasing environmental pressure of anthropogenic CO2 emissions is impeding the sustainability of urban agglomerations (UAs). Recent research has shown that the spatial clustering of UA elements reduces CO2 emissions but underestimates its impact on vegetation carbon sequestration. Using an extended IPAT equation analysis framework and the Logarithmic Mean Divisia Index decomposition approach, this study revealed the positive effects of the economy and population spatial clustering on carbon footprint pressure (CFP) mitigation. Specifically, improving economic spatial clustering mitigated the rise in UA's CFP caused by affluence and population growth. Furthermore, population clustering in core cities effectively mitigated CFP in neighboring cities. Additionally, we found that the efficiency improvement, i.e., the decrease in the ratio of carbon emissions and gross domestic product, should be the dominant driver of CFP mitigation, followed by improved vegetation carbon sequestration. However, these drivers have limited future potential. We believe that by improving UA's spatial clustering of the economy and population, future urban environmental pressures and climate risks will be mitigated.

Green Growth, Carbon Intensity Regulation, and Green Total Factor Productivity in China

Based on input-oriented Malmquist productivity index and parametric decomposition approach, this paper measures China’s green total factor productivity (TFP) index and its growth sources using a panel dataset of 30 provinces of China mainland from 1997 to 2014, and assesses the effect of CO2 intensity regulation on the green TFP growth in China. The results show that the green TFP has been growing at a yearly averaged rate of -1.51% during this period. The results also indicate that the policy of CO2 intensity regulation does not generate significant effect on the green total factor productivity of China’s provinces when using the two stage least squares (2SLS) estimator to control for the potential endogeneity biases. On the other hand, there exists significant heterogeneity in the effect of the CO2 intensity regulation on the green TFP of China’s provinces. Specifically, the CO2 intensity regulation promotes the green development performance of provinces in the eastern area, while it does not generate obvious impacts on the green TFP of provinces in both central and western areas.

Estimation of CO2 Emissions Embodied in Domestic Trade and Their Influencing Factors in Japan

CO2 emissions embodied in domestic trade between Japanese prefectures are gradually increasing and becoming an important growth point in the country’s CO2 emissions. The primary objective of this study is to evaluate the CO2 emissions embodied in Japan’s domestic imports and exports to visualize the carbon transfer paths between prefectures according to the attributes of production and consumption: also to identify the influencing factors of the carbon flow. This study estimated the CO2 emissions embodied in domestic imports and exports by prefectures using input–output analysis, followed by the log-mean Divisia index decomposition approach, which is used to quantify the influencing factor of net export CO2 emissions across prefectures. The results show substantial regional differences in the CO2 emissions embodied in domestic imports and exports across prefectures. Manufacturing prefectures satisfy most of Japan’s domestic demand for industrial products and are the main net exporters of CO2 emissions. Carbon flow is more obvious in economically advanced regions (such as the Kanto and Kansai regions) and covers more prefectures through carbon transfer. Consumer prefectures import the most CO2 emissions and export large amounts of CO2 emissions to other prefectures. Among the three factors influencing net export CO2 emissions, the technology effect has the most significant impact through the carbon intensity of domestic trade flows. These findings highlight the substantial differences in CO2 emissions embodied in domestic trade and the influencing factors across prefectures in Japan. The responsibility for emission reduction is attributable to both manufacturing and consumer prefectures.

Disentangling the sources of dynamics in the agricultural output of the BRIICS and EU countries: The ecological footprint perspective with Shapley value decomposition

Agricultural production and productivity are important from multiple perspectives, including environmental protection, food self-sufficiency, renewable energy sources as well as economic returns. The earlier literature has sparsely addressed the biological and economic productivity dynamics when decomposing the changes in the output of agriculture within a single framework at the country level. This paper presents an index decomposition approach that allows explaining the changes in agricultural output from the perspective of the ecological footprint and biological capacity. These measures represent the shift towards a more valuable output mix and lower environmental pressures. Economic and biological productivity is involved in the analysis. The case of the selected European Union (EU) and BRIICS (Brazil, Russia, India, Indonesia, China and South Africa) countries is considered for the empirical analysis. The index decomposition analysis model based on the Shapley value is constructed for the empirical analysis. The results suggest that the EU countries saw a less vibrant growth in the agricultural output than that of the BRIICS countries over 1992–2016. The biological productivity growth was more important for the EU countries if opposed to the BRIICS ones.

Effect of IQOS introduction on Philip Morris International cigarette sales in Spain: a Logarithmic Mean Divisa Index decomposition approach

ObjectivePhilip Morris International, has already introduced its heated tobacco product, IQOS, in many countries and marketed it on the grounds that it is a less harmful alternative to health. The company claims that its intention is for its brand's traditional cigarette smokers to replace these with IQOS has rarely been independently tested. MethodUsing time series data from September 2016 to June 2020, we analyze whether Heets sales have been accompanied by an improvement in the position of Philip Morris International in the market or if they have merely replaced lost sales of the rest of the brands sold by that tobacco company. ResultsSales of traditional cigarettes of all the brands marketed by PMI have been replaced by IQOS since the introduction of this heated tobacco product in Spain. Almost all of the variations observed in IQOS sales are due to the positioning of this product as a substitute for the range of traditional cigarettes marketed by Philip Morris International. ConclusionsAs there is still no consensus that HTPs are explicitly less harmful to health, health authorities must control messages suggesting improved health outcomes thanks to HTP usage when compared to traditional cigarettes. Such messages could generate a false sense of security and lead to an increase in the consumption of tobacco. In Spain Heets in a category that has a lower tax burden than the category of traditional cigarettes. Tax authorities must consider this migration and the impact this may have on tax collection.

Analysis of Energy Substitution vis-a-vis Security Policy Trade-off with the Emissions Embodied in Bilateral Trade: An Index Decomposition Approach

The trade-off between climate protection and energy security is more striking for the developing countries those are having fewer resources to combat the risk of sudden supply disruptions of energy, however, its reflection in the literature is not found sufficient. This paper aims at exploring this trade-off by uniquely representing the India-UK bilateral trade and applies a spatial index-decomposition exercise of the emissions embodied in the net export. The calculated emission imbalance implied in India-UK bilateral trade is decomposed into the contributions from five important drivers. The study compares the policy trade-offs under three hypothetical scenarios where India is adopting prudent policy measures imitating the UK. Based on these scenario experiments, the study suggests a decision trick where India is adopting a lower energy intensity of input use by altering its energy consumption level keeping the employment of inputs unchanged.

Spatiotemporal carbon emissions across the spectrum of Chinese cities: Insights from socioeconomic characteristics and ecological capacity

In-depth investigation of the spatiotemporal driver patterns of city carbon emissions is vital toward establishing carbon neutrality, as such knowledge would aid policymakers in formulating differentiated emission reduction policies. Through developing a unique carbon emission dataset and applying a spatiotemporal logarithmic mean Divisia index decomposition approach, we explored the spatiotemporal drivers of CO2 emission for diverse cities in China categorized by economic structure and population size during 2002–2018. The results highlighted GDP per capita and industrial structure as the most positive and negative drivers, respectively, with the former overweighing the latter before 2016. Furthermore, the between-group differences of cities categorized using population size were higher than differences within groups, implying evident heterogeneity of carbon emissions. Emission related to within-differences in net primary productivity (NPP) constitutes the largest contributing factor promoting carbon emission in megacities and highly industrialized cities, whereas NPP between-differences in agricultural carbon intensity are predominantly associated with inhibiting emissions in large and highly commercialized cities. We therefore suggest that policymakers should optimize the industrial structure in highly industrialized cities and develop carbon sequestration in cities with high vegetation coverage through fiscal transfer for achieving carbon neutrality.

Does government financial support decrease the inefficiency of public universities? A decomposition approach

This study contributes to the literature by considering for the first time the link between government financial support and the efficiency of public universities in Vietnam. Using the Färe-Primont index decomposition approach, the study shows that the decline in the aggregate efficiency of the universities was driven by a decline in technical efficiency and in residual mix efficiency. Our analysis further reveals that while an input-based government funding system is found to decrease scale efficiency, an increase in the investment ratio for academic and research activities promotes the aggregate, allocative efficiency of public universities.

Greater inequalities in dental caries treatment than in caries experience: a concentration index decomposition approach

BackgroundThe aim of the current study was to (a) measure the socioeconomic inequalities in oral health and examine whether the inequalities are greater in disease experience or in its treatment and to (b) decompose the factors that influence oral health inequalities among the adults of Guangdong Province.MethodsA cross-sectional study was conducted among 35- to 44-year-old and 65- to 74-year-old adults in Guangdong Province. All participants underwent oral health examinations and answered questionnaires about their oral health. We measured the concentration indices of the DMFT and its separate components, namely, decayed teeth (DT), missing teeth (MT), and filled teeth (FT), to explore the inequalities in oral health status; then, we analysed its decomposition to interpret the factors that influence the inequalities.ResultsThe results showed that significant inequality was concentrated on FT (CI = 0.24, 95% CI = 0.14/0.33, SE = 0.05). The concentration indices for the DMFT (CI = 0.02, 95% CI = 0.02/0.06, SE = 0.02) and MT (CI = 0.02, 95% CI 0.03/0.08, SE = 0.03) were small and close to zero, while the concentration for DT (CI = − 0.04, 95% CI = − 0.01/0.02, SE = 0.03) was not statistically significant. The results from the decomposition analysis suggested that a substantial proportion of the inequality was explained by household income, high education level, regular oral examination and type of insurance (5.1%, 12.4%, 43.2%, − 39.6% (Urban Employee Basic Medical Insurance System) and 34.5% (New-Type Rural Medical Collaboration System), respectively).ConclusionsThe results indicated greater inequalities in dental caries than in caries experience. Among the included factors, household income, high education level, and regular oral health examinations had the greatest impact on the inequalities in the number of FT. In addition, the current medical insurance systems, including the Urban Employee Basic Medical Insurance System, Urban Resident Basic Medical Insurance System, and the New-Type Rural Medical Collaboration System, have not been effectively used in oral treatment. Policy-making and the implementation of interventions for tackling socioeconomic oral health inequalities should focus on reducing the burden of treatment and providing greater access to dental care for low-income groups. Welfare policies are skewed towards rural areas and low-income people.

Impacts of the integrated pattern of water and land resources use on agricultural greenhouse gas emissions in China during 2006–2017: A water-land-energy-emissions nexus analysis

The exploitation and utilization of agricultural water-land resources are important sources of greenhouse gas (GHG) emissions in agricultural production. The study of water-land-energy-emission systems can provide an important basis for reducing agricultural GHG emissions. Based on calculations of agricultural CO2e emissions in the 30 provinces of China from 2006 to 2017, this study explores the contribution of the integrated patterns of water and land resources (IPWL), agricultural carbon emission intensity, and economic output per unit water resources to agricultural CO2e emissions per unit sown area using a spatiotemporal index decomposition approach. The conclusions are as follows. (1) In 2006–2017, the IPWL in China fluctuates, increasing from 1.19 × 106 m3/km2 to 1.35 × 106 m3/km2 and is generally distributed as “high in the south and low in the north.” (2) In the temporal domain, a comparison between the periods 2006–2011 and 2006–2017 shows that, with the increase in IPWL, fewer provinces inhibit the IPWL to agricultural CO2e emissions per unit sown area; furthermore, this effect has been weakened in seven provinces. (3) In the spatial domain, the higher the IPWL is in most areas in China, the higher the contribution rate of IPWL is to agricultural CO2e emissions per unit sown area. Finally, several suggestions are offered for mitigating agricultural GHG emissions in China.

Factor Decomposition and Regression Analysis of the Energy Related Carbon Emissions in Shandong, China: A Perspective of Industrial Structure

An in-depth study of the energy related carbon emissions has important practical significance for carbon emissions reduction and structural adjustment in Shandong Province and throughout China. Based on the perspective of industrial structure, the expanded KAYA equation to measure the energy related carbon emissions of the primary industries (Resources and Agriculture) and secondary industries (Manufacturing and Construction) and tertiary industries (Retail and Service) was utilized in Shandong Province from 2011 to 2017. The carbon emissions among industries in Shandong Province were empirically analyzed using the Logarithmic Mean Divisia Index decomposition approach. The results were follows: (1) Under the three industrial dimensions, the energy structure effect and the energy intensity effect have a restraining influence on the carbon emissions of the three industries. (2) The development level effect and the employment scale effect play a pulling role in carbon emissions. (3) From the perspective of the employment structure effect of the primary industry, there is a restraining effect on carbon emissions, while the employment structure effects of the secondary and tertiary industries play a pulling role in carbon emissions, and the employment structure effect of the tertiary industry has a greater pulling effect on carbon emissions than the secondary industry.

Spatial-temporal characteristics and influencing factors of atmospheric environmental efficiency in China.

This research constructs a super efficiency slack-based measure (SBM) model based on the Malmquist-Luenberger (ML) index to analyze the atmospheric environmental efficiency (AEE) of 30 provinces in China from 2000 to 2016 and explores the spatial and temporal differences of AEE by using the coefficient of variation method. This paper further analyzes the internal influencing factors of AEE via the ML index decomposition approach and establishes a panel data regression model to explore AEE's influencing factors in China. The results show some regional differences of the AEE level in China, with it the best in the eastern region and followed in order by the western and central region, and these differences exhibit an increasing trend year by year. During the study period, the development trend of AEE in China is similar to that in the eastern and western regions, showing a "W" shape, where in the central region it has a "U" pattern. The conclusion is that technical progress (TC) is the dominant factor affecting AEE, technical efficiency (EC) fails to effectively promote AEE improvement, and TC and EC present varying degrees of influence and different directions of action in the regions. The analysis results show that the influence effect of economic development on AEE presents a "U" pattern of first declining and then rising. The degree of China opening up to the outside world and its carbon dioxide emissions intensity have significant negative effects on AEE, whereas the increase of pollution control input effectively improves AEE.

Driving factors of CO2 emission inequality in China: The role of government expenditure

China has reached a consensus regarding the total control of carbon dioxide (CO2) emissions; however, regional emission inequalities still exist. The reduction of carbon emissions is a public good and indicates a strong positive externality, which is difficult to solve within the market. Such reductions are highly dependent on governmental contributions. Therefore, using the Theil index and the logarithmic mean Divisia index decomposition approach, this paper integrates government expenditure into an analysis framework, investigating the driving factors of emission inequality and the status and changes of China's CO2 emission inequality from 2007 to 2015, attributing emission inequality to disparities in governmental expenditures, energy consumption, and other socioeconomic factors. The empirical results show that imbalances in economic development, population distribution, and energy structure were prerequisites for a regional emission inequality, while disparities in government expenditure also played an important role. Among these factors, disparities in the expenditure structure were the main cause for emission inequality. The findings of this paper provide guidelines for the government to set carbon emission reduction quota and implement reasonable differentiated emission reduction policies.

The ‘pure’ and structural contributions to the average farm size growth in the EU: The index decomposition approach

Abstract The average farm size is an important indicator of agricultural sustainability. Over the last decades, farmers in the European Union (EU) Member States faced multiple changes of business environment that fuelled shifts in agricultural land use and farm structure. The aim of this paper is to develop and employ a novel index decomposition analysis framework that allows decomposing the changes in the average farm size into pure farm size change and structural effects (specialization and spatial distribution). The empirical research covers the period of 2005–2016 and considers the three levels of aggregation: the EU, Member States, and farming types. Results indicate a remarkable growth in the average farm size at the EU level over 2005–2016. Chain-linked analysis shows that the steepest increase in the average farm size is observed following switch from coupled to decoupled direct payments. Findings suggest that the most serious increase in the average farm size was observed for field crop and specialist grazing livestock farms. Although the main effect contributing to the change in the average farm size at the EU level was the pure increase in the average farm size, results confirm that structural effects also played an important role. However, the contribution of structural effects varies across types of farming and the Member States.

Determinants of Energy-Based CO2 Emissions in Ethiopia: A Decomposition Analysis from 1990 to 2017

Ethiopia, among the fastest growing economies worldwide, is witnessing rapid urbanization and industrialization that is fueled by greater energy consumption and high levels of CO2 emissions. Currently, Ethiopia is the third largest CO2 emitter in East Africa, yet no comprehensive study has characterized the major drivers of economy-wide CO2 emissions. This paper examines the energy-related CO2 emissions in Ethiopia, and their driving forces between 1990 and 2017 using Kaya identity combined with Logarithmic Mean Divisia Index (LMDI) decomposition approach. Main findings reveal that energy-based CO2 emissions have been strongly driven by the economic effect (52%), population effect (43%), and fossil fuel mix effect (40%) while the role of emission intensity effect (14%) was less pronounced during the study period. At the same time, energy intensity improvements have slowed down the growth of CO2 emissions by 49% indicating significant progress towards reduced energy per unit of gross domestic product (GDP) during 1990-2017. Nonetheless, for Ethiopia to achieve its 2030 targets of low-carbon economy, further improvements through reduced emission intensity (in the industrial sector) and fossil fuel share (in the national energy mix) are recommended. Energy intensity could be further improved by technological innovation and promotion of energy-frugal industries.