Adoption of digital repositories for CO2 emissions reduction: the case of Korea

This study aims to estimate the potential economic benefits, energy and CO₂ emissions reductions when using trusted third-party digital repository (TTPR) services in one individual bank, and within the banking industry in Korea. First, the cost, benefit and net benefit of using TTPR services in the banking industry are estimated. Second, the net induced output effect is estimated. Third, based on an environmentally extended input–output analysis, CO₂ emissions reduction was estimated as 1924.32 tons in 2009 and the energy consumption reduction as 640.70 TOE. Fourth, the total economic benefit, which is the sum of the net induced output effect and economic value of CO₂ emissions reductions, is approximately $11.04 million. The findings demonstrate that energy consumption and CO₂ emissions reductions are meaningful enough to result in significant economic benefits. Therefore, the Korean government should promote the use of TTPR services in the entire industry.     

The carbon footprint of UK households 1990-2004: A socio-economically disaggregated, quasi-multi-regional input-output model

This paper presents a socio-economically disaggregated framework for attributing CO₂ emissions to people's high level functional needs. Based around a quasi-multi-regional input-output (QMRIO) model, the study, in theory, takes into account all CO₂ emissions that arise from energy used in production of goods and services to satisfy UK household demand, whether the emissions occur in the UK or abroad. Results show that CO₂ emissions attributable to households were 15% above 1990 levels in 2004, and that although absolute decoupling occurred between household expenditure and CO₂ during the UK's switch from coal to gas in the early 1990s, since then only slight relative decoupling is evident. The proportion of CO₂ that arises outside UK borders in support of UK consumption is rising, and reducing these emissions is particularly problematic in a global trading system. Investigation into the carbon footprint of different segments of the UK population shows wide variation: the segment with the highest carbon footprint emits 64% more CO₂ than the segment with the lowest. Results show that recreation and leisure are responsible for over one quarter of CO₂ emissions in a typical UK household in 2004. We conclude that expanding lifestyle aspirations are significant factors in driving household CO₂ emissions, but the study also emphasizes that attention must be paid to the infrastructures and institutions that result in considerable amounts of CO₂ being locked up in basic household activities through which people meet their everyday needs for subsistence, protection, and communication with family and friends. The findings highlight the sheer scale of the challenge facing UK policy-makers, and suggest that policies should be targeted towards segments of society responsible for the highest carbon footprints.     

Decomposition of energy-related CO2 emission over 1991-2006 in China

This paper presents a decomposition analysis of energy-related CO₂ emission in China for the period 1991-2006 divided into three equal time intervals. The complete decomposition method developed by Sun is used to analyze the nature of the four factors: CO₂ intensity, energy intensity, structural changes and economic activity. The results show that economic activity has the largest positive effect in CO₂ emission changes in all the major economic sectors and China has achieved a considerable decrease in CO₂ emission mainly due to the improved energy intensity. However, the impact of CO₂ intensity and structural changes is relatively small. Structural changes only exhibit positive effect to the CO₂ mitigation in agricultural sector, and CO₂ intensity also contributes to the decrease of CO₂ emission in transportation sector. Moreover, a formula about CO₂ mitigation is presented in this paper, which shows that China has made a significant contribution to reducing global CO₂ emission.     

Does financial development reduce CO2 emissions in Malaysian economy? A time series analysis

This study deals with the question whether financial development reduces CO₂ emissions or not in case of Malaysia. For this purpose, we apply the bounds testing approach to cointegration between the variables. We establish the presence of significant long-run relationships between CO₂ emissions, financial development, energy consumption and economic growth. The empirical evidence also indicates that financial development reduces CO₂ emissions. Energy consumption and economic growth add in CO₂ emissions. The Granger causality analysis reveals the feedback hypothesis between financial development and CO₂ emissions, energy consumption and CO₂ emissions and, between CO₂ emissions and economic growth.     

Norwegian Emissions of CO2 1987–1994 A Study of Some Effects of the CO2 Tax

Several countries have introduced taxes on fossil fuels with the aim of reducing atmospheric emissions, partly because of local environmental goals (SO₂, NO_x) and partly to participate in a global effort to reduce emissions of greenhouse gases. Many macroeconomic studies, based on both global and national models, have been made of how emissions can be reduced with the help of taxes and the consequent reduction in GDP following the introduction of such taxes. Norway has had a CO₂ tax for five years, thereby providing a unique opportunity to evaluate the effects of this tax on emissions. The paper provides a counterfactual analysis of energy consumption and emissions if no CO₂ taxes had been introduced, compared with the actual situation in which such taxes exist. The effect of a CO₂ tax on oil consumption, and thus CO₂ emissions is studied on the basis of partial economic models for various sectors of the Norwegian economy. The study indicates that the CO₂ tax has had an impact on CO₂ emissions in Norway.     

CO2-Stabilization May Be a 'No-Regrets' Policy

Restricting CO₂ emissions requires changing today's consumption pattern away from energy and emission intensive commodities towards cleaner goods. The cost of stabilizing CO₂ emissions at the 1990 level by the year 2000, say, as compared to a business-as-usual trend, is estimated by several researchers to be on the order of 1% of GNP. We will argue that the cost may be overestimated because of a too simple model describing the working of the economic system and the evaluation of welfare. We demonstrate that by expanding a model to include the actual tax system and negative externalities, the cost to present generations from restricting emissions by a CO₂ tax may be negative. That is, some reduction may actually correspond to a 'no-regrets' policy. The reasons are inefficiencies in today's tax system and non-optimal handling of negative externalities. Our analysis suggests that a CO₂ tax and reduced emissions will lessen such inefficiencies.     

A decomposition analysis of CO2 emissions in the United States

This article decomposes the growth in US CO₂ emissions by state. Using the Logarithmic Mean Divisia Index (LMDI) method, we account for CO₂ emissions change in each state between 1990 and 2004. The change is decomposed into five effects: (a) emissions per unit of fossil fuel; (b) share of fossil fuel in total energy consumption; (c) energy intensity; (d) gross state product per capita and (e) population. Results show that for the past 15 years gains in the efficiency of energy use in the economy, the lowering share of fossil fuels in total energy consumption and lowering of emissions intensity of fuels all contributed to offsetting the effect of Gross Domestic Product (GDP) per capita and the population growth in carbon emission across the US.     

Economic Growth and CO2 Emissions in the European Union

This paper examines the relationship between economic growth and CO₂ emissions in the European Union. A panel data analysis for the period 1981 to 1995 is applied in order to estimate the relationship between Gross Domestic Product (GDP) growth and CO₂ emissions in ten selected European countries. The analysis shows important disparities between the most industrialised countries and the rest. The results do not seem to support a uniform policy to control emissions; they rather indicate that a reduction in emissions should be achieved by taking into account the specific economic situation and the industrial structure of each EU member state.     

Quantification of the environmental impacts of road conditions in Brazil

This study evaluates the impacts of Brazilian highway conditions on fuel consumption and, consequently, on carbon dioxide (CO₂) emissions. For the purpose of this study, highway conditions refer to the level of highway maintenance: the incidence of large potholes, large surface cracks, uneven sections, and debris. Primary computer collected data related to the fuel consumption of three types of trucks were analyzed. The data were derived from 88 trips taken over six routes, each route representative of one of two highway conditions: better or worse. Study results are initially presented for each type of truck being monitored. The results are then aggregated to approximate the entire Brazilian highway network. In all cases, results confirmed environmental benefits resulting from travel over the better routes. There was found to be an increase in energy efficiency from traveling better roads, which resulted in lower fuel consumption and lower CO₂ emissions. Statistical analysis of the results suggests that, in general, fuel consumption data were significant at *P < 0.05, rejecting the null hypothesis that average fuel consumption from traveling the better routes is statistically equal to average fuel consumption from traveling the worse routes. Improved Brazilian road conditions would generate economic benefits, reduce dependency on and consumption of fossil fuels (due to the increase in energy efficiency), and reduce CO₂ emissions. These findings may have additional relevancy if Brazil needs to reduce carbon dioxide emissions to reach future Kyoto Protocol's emissions targets, which should take effect in January 2013.     

An analysis of China's climate policy using the China-in-Global Energy Model

The primary approach to address climate change in China has been the use of CO₂ intensity targets coupled with targets for low carbon energy deployment. We evaluate the impact of extending similar targets through 2050 on China's energy use profile and CO₂ emissions trajectory using the China-in-Global Energy Model (C-GEM). The C-GEM is a global computable equilibrium model that includes energy and economic data provided by China's statistical agencies, calibration of savings, labor productivity, and capital productivity dynamics specific to China's stage of development, and regional aggregation that resolves China's major trading partners. We analyze the combined impact of extending CO₂ intensity targets, implemented via a cap-and-trade program, and low carbon energy policies (directives for nuclear power expansion and feed-in tariffs for wind, solar, and biomass energy) through 2050. Although with the policy, simulated CO₂ emissions are around 43% lower in 2050 relative to a reference (No Policy) counterfactual, China's CO₂ emissions still increase by over 60% between 2010 and 2050. Curbing the rise in China's CO₂ emissions will require fully implementing a CO₂ price, which will need to rise to levels higher than $25/ton in order to achieve China's stated goal of peaking CO₂ emissions by 2030.     

Renewable energy drivers: a panel cointegration approach

The expected gains from RES deployment to the reduction of carbon dioxide emissions (CO₂) and the cut-off of external dependence of electricity sources could be important. However, it is crucial to understand the determinants of RES growth to help policymakers drawing effective energy polices, involving a commitment of both citizens and governments. In this paper, we use novel panel econometric tools (taking into account structural breaks and cross-section dependence) and find evidence of nonstationary issues and cointegration issues between renewable energy production and its drivers (CO₂ emissions, GDP per capita, energy use and dependency). The results thus reveal that non-stationary issues should be attended, otherwise they could be biased. Using suitable estimators (DOLS, FMOLS) with two different data sets and different proxies and taking common factors into account by MG estimates, we find that there is no environmental concerns effect explaining the growth of renewables in European countries. However, national revenues, energy consumption (demand effect) and energy dependency have a positive impact on renewables deployment. Considering these results, economic assistance (subsidies) might be a mean to increase further the renewables deployment in EU countries and education about renewables deployment is needed.     

Determinants of the global and regional CO2 emissions: What causes what and where?

Using the Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model and an unbalanced panel dataset of 128 countries covering 1990–2014, this study aims to examine the key impact factors (KIFs) of the global and regional carbon dioxide (CO₂) emissions and analyse the effectiveness of non-renewable and renewable energies. Given the potential cross-sectional dependence and slope heterogeneity, a series of econometric techniques allowing for cross-sectional dependence and slope heterogeneity is applied. The overall estimations imply that the KIFs at the global level are economic growth, followed by population size, non-renewable energy, and energy intensity in order of their impacts on CO₂ emissions; conversely, the KIFs at the regional level vary across different regions and estimators. The results also suggest that renewable energy can lead to a decline in CO₂ emissions at the global level. At the regional level, only for two regions (i.e., S. & Cent. America and Europe & Eurasia) renewable energy has a significant and negative effect on CO₂ emissions, which may be affected by the share of renewable energy consumption in the primary energy mix. Finally, the results indicate varied causality relationships among the variables across regions.

Abbreviations: AMG: Augmented mean group; BP: British Petroleum; BRICS: Brazil, Russia, India, China, and South Africa; CCEMG: Common correlated effects mean group; CD: Cross-section dependence; CIPS: Cross-sectionally augmented Im, Pesaran, and Shin; CO₂: Carbon dioxide; PS: Population size; D-H: Dumitrescu-Hurlin; EI: Energy intensity; EU: European Union; EU-5: Germany, France, Italy, Spain, and the United Kingdom; Europe & Eurasia, Europe and Eurasia; GDP: Gross domestic product; IEA: International Energy Agency; KIF: Key impact factor; LM: Lagrange multiplier; Mtoe, Million tonnes oil equivalent; NRE: Non-renewable energy; RE: Renewable energy; S. & Cent. America, South and Central America; STIRPAT: Stochastic Impacts by Regression on Population, Affluence, and Technology; VECM: Vector error correction model; WDI: World Development Indicators     

Do oil consumption and economic growth intensify environmental degradation? Evidence from developing economies

The purpose of this article is to empirically investigate the impact of economic growth, oil consumption, financial development, industrialization and trade openness on carbon dioxide (CO₂) emissions, particularly in relation to major oil-consuming developing economies. This study utilizes annual data from 1980 to 2012 on a panel of 18 developing countries. Our empirical analysis employs robust panel cointegration tests and a vector error correction model (VECM) framework. The empirical results of three panel cointegration models suggest that there is a significant long-run equilibrium relationship among economic growth, oil consumption, financial development, industrialization, trade openness and CO₂ emissions. Similarly, results from VECMs show that economic growth, oil consumption and industrialization have a short-run dynamic bidirectional feedback relationship with CO₂ emissions. Long-run (error-correction term) bidirectional causalities are found among CO₂ emissions, economic growth, oil consumption, financial development and trade openness. Our results confirm that economic growth and oil consumption have a significant impact on the CO₂ emissions in developing economies. Hence, the findings of this study have important policy implications for mitigating CO₂ emissions and offering sustainable economic development.     

Input-output analysis of carbon emissions embodied in China-Japan trade

Energy-related CO₂ emissions embodied in international trade have been widely studied by researchers all over the world. By using the bilateral trade input–output (BTIO) approach, this study investigates the CO₂ emissions embodied in China–Japan trade during 1995–2009 and attempts to identify the driving forces for the change in CO₂ emissions embodied in China’s exports to Japan during that period by using structural decomposition analysis (SDA). Result shows that CO₂ emissions embodied in China’s exports increased by about 100% from 1995 to 2009, whereas those embodied in China’s imports increased by about 500% during the same period. Result of this research also reveals that the scale effect had a large influence on the increase in CO₂ emissions embodied in China–Japan trade. The technical effect greatly decreased CO₂ emissions embodied in China’s exports to Japan, but obviously increased those embodied in imports. The influence of the structural effect was relatively small and insignificant in the change of CO₂ emissions embodied in China’s exports to Japan, but was notable in the change of emissions embodied in imports.     

The control of CO2 emissions and its economic impact: An AGE model for a german state

Since it is believed that CO₂ is responsible for 55% of the greenhouse effect, a CO₂ levy is now under consideration in several countries. For an assessment of the macroeconomic implications of an integrated energy and environmental policy we employ an applied general equilibrium model (AGE) since all sectors of an economy and all private households contribute to CO₂ emission. Our model is a temporary equilibrium model with capacity extension under adjustment costs and with abatement activities for SO₂ and NO_x emissions.The model of consumer behavior will result in a system of consumer demand functions for non-durables as well as for durable goods. The simulations show the cost of inefficiency in resource allocation if CO₂ taxes differ between industries and households. We finally present the marginal cost curve of CO₂ emission reduction.     

Over-Allocation or Abatement? A Preliminary Analysis of the EU ETS Based on the 2005–06 Emissions Data

This paper provides an initial analysis of the EU ETS based on the installation-level data for verified emissions and allowance allocations in the first 2 years of the first trading period. These data reveal that CO₂ emissions were about 3% lower than the allocated allowances. The main objective of the paper is to shed light on the extent to which over-allocation and abatement have taken place in 2005 and 2006, when a significant CO₂ price was observed. We propose a measure by which over-allocation can be judged and provide estimates of abatement based on emissions data and indicators of economic activity as well as trends in energy and carbon intensity. Finally, we discuss the insights and implications that emerge from this tentative assessment. The ideas expressed in this paper are those of the authors and do not necessarily represent views of the International Energy Agency or its Member Countries.     

Time-varying correlations in oil,gas and CO2 prices: an application using BEKK,CCC and DCC-MGARCH models

Previous literature has identified oil and gas prices as being the main drivers of CO₂ prices in a univariate Generalized Autoregressive Conditional Heteroscedasticity (GARCH) econometric framework (Alberola et al., 2008; Oberndorfer, 2009). By contrast, we argue in this article that the interrelationships between energy and emissions markets shall be modelled in a Vector Autoregressive (VAR) and Multivariate GARCH (MGARCH) framework, so as to reflect the dynamics of the correlations between the oil, gas and CO₂ variables overtime. Using the Baba–Engle–Kraft–Kroner (BEKK), Constant Conditional Correlation (CCC) and Dynamic Conditional Correlation MGARCH (DCC-MGARCH) models on daily data from April 2005 to December 2008, we highlight significant own-volatility, cross-volatility spillovers, and own persistent volatility effects for nearly all markets, indicating the presence of strong Autoregressive Conditional Heteroscedasticity (ARCH) and GARCH effects. Besides, we provide strong empirical evidence of time-varying correlations in the range of [?0.3;?0.3] between oil and gas, [?0.05;?0.05] between oil and CO₂, and [?0.2;?0.2] between gas and CO₂, that have not been considered by previous studies. These findings are of interest for traders and utilities in the energy sector, but also for a broader applied economics audience.     

CO2 emissions in Australia: economic and non-economic drivers in the long-run

Australia has sustained a relatively high economic growth rate since the 1980s compared to other developed countries. Per capita CO₂ emissions tend to be highest amongst OECD countries, creating new challenges to cut back emissions towards international standards. This research explores the long-run dynamics of CO₂ emissions, economic and population growth along with the effects of globalization tested as contributing factors. We find economic growth is not emission-intensive in Australia, while energy consumption is emissions intensive. Second, in an environment of increasing population, our findings suggest Australia needs to be energy efficient at the household level, creating appropriate infrastructure for sustainable population growth. High population growth and open migration policy can be detrimental in reducing CO₂ emissions. Finally, we establish globalized environment has been conducive in combating emissions. In this respect, we establish the beneficial effect of economic globalization compared to social and political dimensions of globalization in curbing emissions.     

Structural decomposition analysis and input-output subsystems: Changes in CO2 emissions of Spanish service sectors (2000-2005)

The analysis of gas emissions by an input-output subsystem approach provides detailed insight into pollution generation in an economy. Structural decomposition analysis, on the other hand, identifies the factors behind the changes in key variables over time. Extending the input-output subsystem model to account for the changes in these variables reveals the channels by which environmental burdens are caused and transmitted throughout the production system. In this paper we propose a decomposition of the changes in the components of CO₂ emissions captured by an input-output subsystems representation. The empirical application is for the Spanish service sector, and the economic and environmental data are for years 2000 and 2005. Our results show that services increased their CO₂ emissions mainly because of a rise in the emissions generated by non-services to cover the final demand for services. The decomposed effects show a decrease in CO₂ emissions due to technological changes between 2000 and 2005 compensated by an increase in emissions caused by the rise in final demand of services. Finally, large asymmetries exist not only in the quantitative changes in the CO₂ emissions of the various services but also in the decomposed effects of these changes.     

Is high-speed rail heading towards a low-carbon industry? Evidence from a quasi-natural experiment in China

Existing studies have investigated the environmental dividends of substituting high-speed rail (HSR) for other energy-intensive vehicles from an engineering standpoint, but they have yet to explore the economic effects of HSR and the associated carbon emissions reduction benefits. To fill the research gap, we use panel data from 285 Chinese cities between 2004 and 2014, and employ a spatial difference-in-differences model to empirically examine the impact of HSR opening on industrial CO₂ emissions. After controlling for spillover effects from neighboring HSR cities, our results show that cities offering HSR services significantly reduce their own industrial CO₂ emissions. This finding is robust and is unaffected by outliers, control group selection, time trends, geography and expectation factors, or endogeneity. The mechanism test reveals that the structural transformation effect, technological innovation effect, and investment attractiveness effect are three intermediate influence channels. Further research finds that the emissions reduction benefit increases as the spatial and temporal intensities of HSR openings ascend the ladder, and HSR services have a spillover effect within a 300-kilometer radius. Moreover, the carbon benefit of China’s HSR far surpasses its carbon footprint, indicating that China’s HSR is green after accounting for economic emissions reductions that were often neglected in prior research. Based on these findings, we recommend that China accelerate HSR expansion in order to reduce carbon emissions in a scientific and responsible manner.