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| 1 |
ID:
150793
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| Summary/Abstract |
Enhancing energy technology innovation performance, which is widely measured by energy technology patents through energy technology research and development (R&D) activities, is a fundamental way to implement energy conservation and emission abatement. This study analyzes the effects of R&D investment activities, economic growth, and energy price on energy technology patents in 30 provinces of China over the period 1999–2013. Several unit root tests indicate that all the above variables are generated by panel unit root processes, and a panel cointegration model is confirmed among the variables. In order to ensure the consistency of the estimators, the Fully-Modified OLS (FMOLS) method is adopted, and the results indicate that R&D investment activities and economic growth have positive effects on energy technology patents while energy price has a negative effect. However, the panel error correction models indicate that the cointegration relationship helps to promote economic growth, but it reduces R&D investment and energy price in the short term. Therefore, market-oriented measures including financial support and technical transformation policies for the development of low-carbon energy technologies, an effective energy price mechanism, especially the targeted fossil-fuel subsidies and their die away mode are vital in promoting China's energy technology innovation.
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| 2 |
ID:
149909
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Facing with the increasing contradiction of economic growth, energy scarcity and environmental deterioration, energy conservation and emissions abatement have been ambitious targets for the Chinese government. Improving energy efficiency through technological advancement is a primary measure to achieve these targets. However, the existence of energy rebound effects may completely or partially offset energy savings associated with technological advancement. This paper adopted a modified input-output model to estimate the economy-wide energy rebound effects across China's economic sectors with the consideration of energy subsidies. The empirical results show that the aggregate rebound effect of China is about 1.9% in 2007–2010, thus technological advancement significantly restrains energy consumption increasing. Removing energy subsidies will cause the aggregate rebound effect declines to 1.53%. Specifically, removing subsidies for coal and nature gas can reduce the rebound effects signifcantly, while removing the subsidies for oil products has a small impact on rebound effect. The existence of rebound effects implies that technological advancement should be cooperated with energy price reform so as to achieve the energy saving target. In addition, the government should consider the diversity of economic sectors and energy types when design the reform schedule.
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| 3 |
ID:
143375
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| Summary/Abstract |
This study proposes an improved method for measuring green productivity growth in order to overcome the “discriminating power problem” and “technical regress” associated with the conventional data envelopment analysis (DEA) models. The rationale is to combine the concepts of super-efficiency and sequential DEA models to subsequently construct an improved production possibility set for the directional distance function (DDF). With this enhancement, the Malmquist–Luenberger productivity index (MLPI), which can be compared across sections and periods, is proposed. Therefore, the correct technical and efficiency change components can be obtained after decomposing the MLPI. This novel MLPI is employed to measure the green productivity growth of 36 Chinese industrial subsectors during the period 1998–2011, under the constraint of energy consumption and CO2 emissions. A comparison of the measures of the current study with the productivity growth indexes that have been previously used yielded the following results: (i) productivity growth rate is overestimated without considering CO2 emissions; (ii) the rates of technical and efficiency changes are under- and over-estimated respectively, and (iii) the rate of green productivity growth is also underestimated by the previous indexes. The main conclusions and its policy implications for China's green productivity growth through technology progress and structural adjustment are discussed in-depth.
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