This paper examines the causal relationships between carbon dioxide emissions, energy consumption and real economic output using panel cointegration and panel vector error correction modeling ...techniques based on the panel data for 28 provinces in China over the period 1995–2007. Our empirical results show that CO2 emissions, energy consumption and economic growth have appeared to be cointegrated. Moreover, there exists bidirectional causality between CO2 emissions and energy consumption, and also between energy consumption and economic growth. It has also been found that energy consumption and economic growth are the long-run causes for CO2 emissions and CO2 emissions and economic growth are the long-run causes for energy consumption. The results indicate that China's CO2 emissions will not decrease in a long period of time and reducing CO2 emissions may handicap China's economic growth to some degree. Some policy implications of the empirical results have finally been proposed.
► We conduct a panel data analysis of the energy–CO2–economy nexus in China. ► CO2 emissions, energy use and economic growth appear to be cointegrated. ► There exists bidirectional causality between energy consumption and economic growth. ► Energy consumption and economic growth are the long-run causes for CO2 emissions.
Improving energy efficiency and productivity is one of the most cost-effective ways for achieving the sustainable development target in China. This paper employs non-radial directional distance ...function approach to empirically investigate energy efficiency and energy productivity by including CO2 emissions as an undesirable output. Three production scenarios, namely energy conservation (EC), energy conservation and emission reduction (ECER), and energy conservation, emission reduction and economic growth (ECEREG), are specified to assess China's energy efficiency and productivity growth during the period of Eleventh Five-Year Plan. Our empirical results show that there exist substantial differences in China's total-factor energy efficiency and productivity under different scenarios. Under the ECEREG scenario, the national average total-factor energy efficiency score was 0.6306 in 2005–2010, while the national average total-factor energy productivity increased by 0.27% annually during the period. The main driving force for energy productivity growth in China was energy technological change rather than energy efficiency change.
•China's regional energy efficiency and productivity in 2005–2010 are evaluated.•Three production scenarios are considered.•Non-radial directional distance function with CO2 emissions is employed.•Technological change is the main driver for China's energy productivity growth.
Global awareness on energy security and climate change has created much interest in assessing economy-wide energy efficiency performance. A number of previous studies have contributed to evaluate ...energy efficiency performance using different analytical techniques among which data envelopment analysis (DEA) has recently received increasing attention. Most of DEA-related energy efficiency studies do not consider undesirable outputs such as CO2 emissions in their modeling framework, which may lead to biased energy efficiency values. Within a joint production framework of desirable and undesirable outputs, in this paper we construct both static and dynamic energy efficiency performance indexes for measuring industrial energy efficiency performance by using several environmental DEA models with CO2 emissions. The dynamic energy efficiency performance indexes have further been decomposed into two contributing components. We finally apply the indexes proposed to assess the industrial energy efficiency performance of different provinces in China over time. Our empirical study shows that the energy efficiency improvement in China's industrial sector was mainly driven by technological improvement.
► China's industrial energy efficiency is evaluated by DEA models with CO2 emissions. ► China's industrial energy efficiency improved by 5.6% annually since 1997. ► Industrial energy efficiency improvement in China was mainly driven by technological improvement.
This paper proposes a parametric frontier approach to estimating economy-wide energy efficiency performance from a production efficiency point of view. It uses the Shephard energy distance function ...to define an energy efficiency index and adopts the stochastic frontier analysis technique to estimate the index. A case study of measuring the economy-wide energy efficiency performance of a sample of OECD countries using the proposed approach is presented. It is found that the proposed parametric frontier approach has higher discriminating power in energy efficiency performance measurement compared to its nonparametric frontier counterparts.
The feed-in tariff policy is widely used to promote the development of renewable energy. China also adopts feed-in tariff policy to attract greater investment in solar photovoltaic power generation. ...This study employs real options method to assess the optimal levels of feed-in tariffs in 30 provinces of China. The uncertainties in CO2 price and investment cost are considered. A method that integrates the backward dynamic programming algorithm and Least-Squares Monte Carlo method is used to solve the model. The results demonstrate that the feed-in tariffs of 30 provinces range from 0.68 RMB/kWh to 1.71 RMB/kWh, and the average level is 1.01 RMB/kWh. On this basis, we find that the levels of sub-regional feed-in tariff announced in 2013 are no longer appropriate and should be adjusted as soon as possible. We have also identified the implications of technological progress and carbon emission trading schemes, as well as the importance of strengthening electricity transmission. It has been suggested that the Chinese government takes diverse measures, including increasing research and development investment, establishing and improving a nationwide carbon emission trading scheme and accelerating the construction of electricity-transmission infrastructure, to reduce the required feed-in tariff and promote the development of solar photovoltaic power generation.
•We estimate the optimal levels of feed-in tariffs for 30 provinces in China by using real options method.•The uncertainties in CO2 price and investment cost are considered.•The feed-in tariffs of 30 provinces range from 0.68 RMB/kWh to 1.71 RMB/kWh, and the average level is 1.01 RMB/kWh.
This paper proposes a real options model for evaluating renewable energy investment by considering uncertain factors such as CO2 price, non-renewable energy cost, investment cost and market price of ...electricity. A phase-out mechanism is built into the model to reflect the long-term changes of subsidy policy. We apply the proposed model to empirically evaluate the investment value and optimal timing for solar photovoltaic power generation in China. Our empirical results show that the current investment environment in China may not be able to attract immediate investment, while the development of carbon market helps advance the optimal investment time. A sensitivity analysis is conducted to investigate the dynamics of investment value and optimal timing under the changes of unit generating capacity, subsidy level, market price of electricity, CO2 price and investment cost. It is found that the high investment cost and the volatility of electricity and CO2 prices, are not conducive to attract immediate investment. Instead, increasing the level of subsidy, promoting technological progress and maintaining the stability of market are useful to stimulate investment.
•Propose real option model for evaluating renewable energy investment under uncertainty•Evaluate solar PV power generation in China by considering multiple uncertain factors•Explore the dynamics of value and optimal investment timing by sensitivity analysis
This paper examines the optimal control of CO2 emissions from a perspective of efficiency analysis. Several centralized data envelopment analysis (DEA) models are introduced to study the optimal ...allocation of CO2 emissions under spatial, temporal and spatial–temporal allocation strategies, respectively. The models have been used to determine the optimal paths for controlling CO2 emissions at provincial and regional levels in China. A sensitivity analysis of the optimal path on the emission control coefficient under spatial–temporal allocation strategy is further carried out. Our empirical results show that more developed regions should take emission reduction responsibility earlier than less developed regions in China. Of the three allocation strategies, spatial–temporal allocation strategy seems to be a better choice for achieving the optimal control of CO2 emissions at country level since it is more encompassing by allowing both timing and spatial substitutions. It is also found that there exists an inverted U-shape relationship between the aggregate optimal GDP and the emission control coefficient, which shows that modest emission reduction policy might be more appropriate for China in order to achieve the joint goals of economic development and CO2 emission reduction.
•The optimal control of CO2 emissions in China is examined.•Centralized DEA models are used to allocate CO2 emissions under different strategies.•More developed regions should implement emission reduction earlier.•Modest emission reduction policy could be more appropriate for China.
Transport sector accounts for about 8% of total energy consumption in China and this share will likely increase in the visible future. Improving energy efficiency has been considered as a major way ...for reducing transport energy use, whereas its effectiveness might be affected by the rebound effect. This paper estimates the direct rebound effect for passenger transport in urban China by using the linear approximation of the Almost Ideal Demand System model and simulation analysis. Our empirical results reveal the existence of direct rebound effect for passenger transport in urban China. A majority of the expected reduction in transport energy consumption from efficiency improvement could be offset due to the existence of rebound effect. We have further investigated the relationship between the magnitude of direct rebound effect and households' expenditure. It was found that the direct rebound effect for passenger transport tends to decline with the increase of per capita household consumption expenditure.
► The magnitude of direct rebound effect for urban passenger transport in China is 96%. ► The rebound effect in China could be larger than that in developed countries. ► The rebound effect in China declined with the increase of per capita expenditure.
The nonparametric data envelopment analysis (DEA) methodology has gained much popularity in assessing carbon emission performance within a joint production framework with energy inputs and CO2 ...emissions. The majority of existing studies, however, neglected the interlinkage between energy inputs and CO2 emissions in their analytical frameworks, which may distort the modeling results. To address this issue, we invoked the weak disposability assumption for both (fossil) energy inputs and CO2 emissions, and developed a new joint production technology that was found in line with the material balance principle and simultaneously allowed for the flexibility of emission abatement options. Built upon the production technology, we developed two indexes to measure carbon emission performance, and proposed a decomposition model to quantify the roles of different options in abating CO2 emissions. We also applied the proposed models to study the carbon emission performance of the world's top 25 CO2 emitters. It was found that carbon emission performance varied across different emitters and different abatement options. Energy efficiency improvement and energy structure adjustment were not of equal importance in pursuing the minimum CO2 emissions.
•Advocate the weak disposability of energy input and CO2 emissions.•Develop DEA models for measuring carbon emission performance under different abatement options.•Examine the role of different abatement options in abating CO2 emissions.•Conduct an application study on the world's 25 top CO2 emitters.
•Provincial marginal abatement cost curves are derived.•The economic performance of interprovincial CO2 emission trading in China is modeled.•Total abatement cost could be reduced by over 40% with ...interprovincial emission trading.•CO2 emission and population criteria look fairer in allocating emission allowances.
Carbon emission reduction is a long-term strategy for China to promote its economic and social development. However, emission reduction often involves a huge amount of technological investment, which could vary substantially across different provinces due to their discrepancy in economic and technological development levels. Emission trading as a useful policy instrument may help different provinces achieve their emission reduction targets cost-effectively. This paper models the economic performance of an interprovincial emission reduction quota trading scheme in China. The marginal abatement cost curve of each province in China is first estimated. A nonlinear programming model is further developed to evaluate the economic performance of interprovincial emission reduction quota trading. Five equity criteria are used to conduct the initial allocation of emission reduction targets between different provinces. Our modeling results show that China’s total emission abatement cost could decrease by over 40% through implementing such an interprovincial emission reduction quota trading scheme. Of the five alternative criteria, the CO2 emissions and population criteria look fairer and are recommended for use in the initial allocation of CO2 emission reduction targets.
