[en] This paper aims to objectively identify the impact of green finance on the green economy of China, and then put forward some suggestions that good for the government to guide the development of green finance, and promote the full play of finance in promoting development of the green economy. Through constructing an index system and a super-efficiency slack-based model, this study measures the level of green financial development and regional ecological efficiency, respectively, for Chinese 30 provinces between 2010 and 2015. On this basis, taking per capita GDP, industrial structure, urbanization rate, and energy efficiency as controlling variables, we construct a varying intercept model and a varying coefficient model. Our primary findings are that the impact of China’s green financial development on regional ecological efficiency is not obvious in general, and the corresponding average influence coefficient is − 0.1847, which is inconsistent with theoretical analysis. Also, other impacts from per capita GDP, industrial structure, urbanization rate, and energy efficiency on ecological efficiency are statistically significant; the coefficients are − 0.1701, 0.3901, 0.5410, and 0.3022, respectively. Moreover, there are significant regional differences in the impacts of green financial development on ecological efficiency. For some provinces, such as Tianjin, Jilin, and Heilongjiang, green financial development significantly promotes ecological efficiency. However, for Beijing, Jiangsu, and Zhejiang, it is inconsistent with theoretical analysis.

[en] In this study, we examine the energy intensity convergence in OECD countries within the context of recent developments in unit root analysis by paying attention to modeling structural shifts. We collect the total primary energy consumption/GDP data of 27 OECD countries during the period 1980–2014. The findings indicate that controlling for shifts plays a crucial role, and different approximations in modeling breaks lead to changes in inferences. In conclusion, we present some policy proposals.

No abstract available

[en] Many papers have been documenting and analysing the asymmetry and the weakening of the oil price-macroeconomy relationship as off the early eighties. While there seems to be a consensus about the factors causing the asymmetry, namely adjustment costs which offset the benefits of low energy prices, the debate about the weakening of the relationship is not over yet. Moreover, the alternative oil price specifications which have been proposed by, and to restore the stability of the relationship fail to Granger cause output or unemployment in post-1980 data. By using the concept of accelerations of the oil price, we show that the weakening of this relationship corresponds to the appearance of slow oil price increases, which have less impact on the economy. When filtering out these slow oil price variations from the sample, we manage to rehabilitate the causality running from the oil price to the macroeconomy and show that far from weakening, the oil price accelerations-GDP relationship has even been growing stronger since the early eighties. (author)

[en] Highlights: • A hybrid approach is presented for the estimation of the electricity demand. • The proposed method integrates the capabilities of GP and SA. • The GSA model makes accurate predictions of the electricity demand. - Abstract: This study proposes an innovative hybrid approach for the estimation of the long-term electricity demand. A new prediction equation was developed for the electricity demand using an integrated search method of genetic programming and simulated annealing, called GSA. The annual electricity demand was formulated in terms of population, gross domestic product (GDP), stock index, and total revenue from exporting industrial products of the same year. A comprehensive database containing total electricity demand in Thailand from 1986 to 2009 was used to develop the model. The generalization of the model was verified using a separate testing data. A sensitivity analysis was conducted to investigate the contribution of the parameters affecting the electricity demand. The GSA model provides accurate predictions of the electricity demand. Furthermore, the proposed model outperforms a regression and artificial neural network-based models

[en] The world's primary energy consumption in the last 40 years has been increasing at 2.2%/year while GDP growth has been 3.4%/years over the same period. The decline of the energy intensity (I=E/GDP) has been, therefore, of 1.2%/year. In order to reduce the world's consumption growth proposal have been made to reduce the world's energy intensity by 40% by 2030 which corresponds to a reduction of 2.5%/year, roughly the double of the historical decline. Our analysis shoes that such goal could only be achieved by an unprecedented reduction of the energy intensity of “services” (which represent less than half the world energy consumption) since energy intensity of industry has remained practically constant in the last 40 years. - Highlights: ► GDP and world's energy consumption are split in 2 main sectors: industry and “services”, etc. ► The evolution of the energy intensity for these sectors since 1971 is calculated. ► The energy intensity of the industry sector is practically constant since 1971. ► All the decline of the energy intensity since 1971 comes from the “services” sector

[en] Equity considerations play an important role in international climate negotiations. While policy analysis has often focused on equity as it relates to mitigation costs, there are large regional differences in adaptation costs and the level of residual damage. This paper illustrates the relevance of including adaptation and residual damage in equity considerations by determining how the allocation of emission allowances would change to counteract regional differences in total climate costs, defined as the costs of mitigation, adaptation, and residual damage. We compare emission levels resulting from a global carbon tax with two allocations of emission allowances under a global cap-and-trade system: one equating mitigation costs and one equating total climate costs as share of GDP. To account for uncertainties in both mitigation and adaptation, we use a model-comparison approach employing two alternative modeling frameworks with different damage, adaptation cost, and mitigation cost estimates, and look at two different climate goals. Despite the identified model uncertainties, we derive unambiguous results on the change in emission allowance allocation that could lessen the unequal distribution of adaptation costs and residual damages through the financial transfers associated with emission trading. (letter)

[en] A large amount of carbon dioxide emissions have drawn more and more attention recently. Existing regional research is mainly based on the classification of geographical location, without considering the differences in urbanization. Using panel data of 30 provinces in China during the period of 1997–2014, this paper investigates the impact of population, per capita GDP, energy intensity, urbanization, industry proportion and tertiary industry proportion on CO₂ emissions. Taking into account regional differences, 30 provinces in China are divided into four regions according to the features of “urbanization–CO₂ emissions.” The results show that the impacts of population and per capita GDP on CO₂ emissions in the LU–LC region are higher than the other three regions. The energy intensity has positive effect on CO₂ emissions in the four regions. The impact of energy intensity on CO₂ emissions in HU–HC and HU–LC regions is greater than the other two regions. Meanwhile, the impact of urbanization on CO₂ emissions differs across regions. The urbanization has a significant negative effect on CO₂ emissions in the HU–LC region, indicating the urbanization increases CO₂ emissions. However, the urbanization has a positive effect on CO₂ emissions in the LU–HC region, indicating the urbanization increases CO₂ emissions in the region. The impact of industry proportion is not statistically significant in all the regions, while the impact of tertiary industry proportion on CO₂ emissions is negatively significant in the HU–LC and LU–HC regions, which indicates that the adjustment and upgrading of industrial structure play important roles in the decrease in carbon emissions.

[en] This paper presents a model to analyze the mechanism of the global contribution of energy usage by product exports. The theoretical analysis is based on the perspective that contribution estimates should be in relatively smaller sectors in which the production characteristics could be considered, such as the productivity distribution for each sector. Then, we constructed a method to measure the global contribution of energy usage. The simple method to estimate the global contribution is the percentage of goods export volume compared to the GDP as a multiple of total energy consumption, but this method underestimates the global contribution because it ignores the structure of energy consumption and product export in China. According to our measurement method and based on the theoretical analysis, we calculated the global contribution of energy consumption only by industrial manufactured product exports in a smaller sector per industry or manufacturing sector. The results indicated that approximately 42% of the total energy usage in the whole economy for China in 2013 was contributed to foreign regions. Along with the primary products and service export in China, the global contribution of energy consumption for China in 2013 by export was larger than 42% of the total energy usage.

[en] Oil is an essential and important energy source and is related to energy security and national strategy. Based on a recursive dynamic computable general equilibrium model, this study examines the potential impacts on the major socioeconomic indices in China, which includes economic growth, price level, employment, household welfare, and production activity, under different imported oil shortage scenarios. Results show that oil shortage has negative impacts on China’s economic growth; if all the extra proceeds from domestic oil price increase is assigned to government budget for compensating investment loss, the negative impacts on GDP will mainly stem from its negative impacts on total consumption; the decrease in labor income plays an obviously greater role in the decrease in total consumption than the effects of an increase in CPI. The negative impacts on rural households are greater than urban households. The profit of most production sectors, and the export of almost all sectors, will be negatively influenced.