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Few studies addressed the relationship between the energy efficiency cycle and the export-oriented economic growth style, and our work aimed to contribute this research in the literature using China's dataset during 1985–2018. Results of the autoregressive-distributed-lag model there were two cycles in China's energy efficiency, and the first ranged from 1989 to 2002 while the second was over the period 2003–2012. Meanwhile, the estimations suggested that a 1% export increase was linked to a 0.107% increase in energy efficiency in the long run. However, the export was significantly and negatively associated with the short-run fluctuation of energy efficiency. As a result, the statistical simulation confirmed that export would raise the fluctuation range of energy efficiency.

This study is designed to investigate the impact of pollution on the inequality in health care expenditure. We use the method of stochastic frontier function to model residents’ demand of health ca...

The scale of urbanization in China has more than doubled in the last two decades, with important consequence of transforming the landscape of energy. While the relationship between urbanization and energy use has been examined extensively, the question of whether urbanization affects energy efficiency receives less attention. In this study, we seek to provide new empirical evidence on the effect of urbanization on energy use and efficiency in China. We extend the stochastic frontier approach to model the demand for energy while measuring energy efficiency by distinguishing between efficient- and inefficient-use. Using data from a variety of sources during 2005–2015 to generate an eleven-year province-level panel, we estimate a simultaneous-equation model through a random effects panel data specification. We find that urbanization in China during our sample period is associated with a significant increase in energy consumption, but there is little evidence of improvement in energy efficiency. In particular, our results from our preferred specification suggest that the inefficient-use accounts for approximately 23% of the total energy consumption.

In China, where environmental regulations are less strict, finance would cause pollution to rise by promoting the growth of polluting industries. Exploiting a Chinese dataset over the period 2004–2014, 1% increase in the finance measured by credits to GDP, would cause pollution to rise by 4.29%, which is fairly large and cannot be ignored, and the results is robust when finance is measured by deposits to GDP. Thus, it is concluded that policies focused on pollution reduction would be ineffective and that policies on promoting finance would fall short of their intention to stimulate economic growth.

There is no consensus about the impact of urbanization on energy efficiency. We seek to fill this gap in literature using data from 78 countries for the period of 1995 through 2012. Extending the Stochastic Impacts by Regression on Population, Affluence, and Technology model, we identify the impact of urbanization on energy consumption and efficiency. Results of generalized method of moments estimation indicate that the process of urbanization leads to substantial increases in both the actual and the optimal energy consumption, but a decrease in efficiency of energy use. In addition, we find that the extent to which energy inefficiency correlates with urbanization is greater in countries with higher gross domestic product per capita.

Our work provides a comprehensive investigation of the coupling between the efficiency of economic growth and the efficiency of carbon emissions reduction in China, and makes a distinction between the coupling over the long-run and the short-run. Our estimates suggested significant evidence of coupling between economic growth and efficiency in carbon emissions reduction in the long-run, but China’s economic growth still increased carbon emissions at the aggregate level. In the short-run, coupling effects were different across provinces that were at different stages of economic development. Provinces with low- and high-stages of development saw positive short-run coupling, but provinces at the intermediate stage of development saw the contrary, which resulted in an obvious “U" shaped relationship between short-run coupling effects and real GDP per capita. Finally, our findings provide an economic rationale for differentiated low-carbon policies.

This paper extends the Stochastic Impacts by Regression on Population, Affluence and Technology (STIRPAT) model to be a panel error-correction model, which allows for a rich dynamic analysis where changes of urbanization account for carbon dioxide emissions. Applying the mean group (MG), pooled mean group (PMG), and dynamic fixed effect (DFE) estimation, we examine a China province-level data over the period from 1995 to 2011. Our estimates indicate that rapid urbanization increases carbon dioxide emissions both in the short-run and in the long-run. However, the lower magnitude of the environmental impact of urbanization in the short-run than that in the long-run indicates that the process of urbanization would have a long-lasting impact on the growth rate of carbon dioxide emissions. In addition, our results suggest that the impact of urbanization on carbon dioxide emissions would usually take some time to materialize fully, and would be useful to policymakers who seek to coordinate economic development and reduction of carbon dioxide emissions.

This paper examines the effect of carbon dioxide (CO2) emissions on economic convergence among Chinese provinces from 1998 to 2012 using the framework of environmental total factor productivity (ETFP). We modify the standard β-convergence model to incorporate undesirable outputs such as CO2 emissions. The bootstrap method is subsequently applied to estimate the values of ETFP, and the system generalized method of moments (GMM) estimator is employed to test for convergence. The results indicate that there is imperfect interregional economic convergence in China, which is supported by gross domestic product (GDP) and CO2 emissions. However, the convergence process is inefficient due to the ‘catching up’ convergence trend of per capita CO2 emissions in China. This paper also finds that the variation in the capital stock and labour does not support the hypothesis that all of the provinces can converge to a steady state.

Reduction of carbon dioxide emission is of great significance to the sustainability of global development. For the developing countries, however, carbon reduction is perceived costly for its possible dampening effect on economic growth. This paper builds a Low-Carbon Development Index to assess the potentials for an economy to improve environmental efficiency of its development by reducing carbon dioxide emission while still achieving economic growth. Applying the index to a data set of 30 Chinese provincial economies from for the period 1998 to 2012, we evaluate the environmental efficiency of China's economic development in terms of carbon dioxide emission and discuss whether it is economically feasible for the country to reduce the country's carbon intensity by 40–45% from the level of 2005, a target committed by its government at the 2009 UN Climate Change Conference (COP15).

This paper extends prior research on energy inefficiency in China by utilizing a unique shadow price framework allocation in 30 Chinese provinces. We estimate the shadow price for energy input using the framework of production, and use the ratio of the shadow price to the market price to describe energy utilization. Using Chinese provincial-level data from 1998 to 2011, the results of the analysis reveal that shadow prices in China have grown rapidly during the sample period, which signifies that China has improved its performance in energy utilization since 1998. However, there are eighteen provinces whose shadow prices are lower than market prices. This result suggests that energy utilization is at a low level in these provinces and can be improved by a reallocation of inputs.

China and the United States of America (US) are developing renewable energy concurrently. In this paper, we seek the opportunities for potential cooperation between these two countries based on the analysis of annual economic data. A mathematical model has been established to characterize correlations among GDP, carbon dioxide emissions, energy prices and the renewable energy cooperation index. Based on statistical analyses, such cooperation can promote economic development, reduce carbon dioxide emissions, improve the environment and realize green growth. If US monetary and technology resources and Chinese markets are combined, benefits can be mutually gained.

Foreign direct investment (FDI) may have a positive effect on the level of pollution in host countries, as described by the pollution haven hypothesis (PHH). However, this kind of effect may depend on the economic conditions in host countries. In this study, we conduct research on the FDI’s effect on China’s CO2 emissions during the market-oriented reform. The results are as follows. Firstly, FDI directly promotes China’s CO2 emissions. Secondly, with market-oriented reform, this positive effect from FDI is lowering year by year, which indicates that the market-oriented reform could alleviate the positive effect of FDI on China’s CO2 emissions. Thirdly, as China’s market-oriented reform was implemented gradually from experimental zones to the whole country, regional market development is uneven, and as such so is FDI’s effect on local CO2 emissions. Provinces in the eastern area generally evidenced higher market development and lower CO2 emissions from FDI, while four provinces in west area evidenced both lower market development and higher CO2 emissions from FDI.

Energy is a nonrenewable resource. Hence, long-term sustainable development cannot be guaranteed by an increase in energy efficiency but to use the least energy as possible. Therefore, this article builds an index of low-energy development (LEDI) to describe the shift from high-energy development to LEDI. This research, which uses Chinese provincial data set, reveals that the LEDI of China is at the low level, but has a significant upward trend after 2005.