In the context of “new normal” economy and frequent “haze”, the strategy of energy conservation and emission reduction aiming to lower costs and reduce pollution is currently still a major strategic direction in China and the world, and will remain so for some time in the future. This paper uses the annual data of West Texas Intermediate (WTI) crude oil price in 1987–2014 as samples. We firstly present the direction and mechanism of the influence of oil price change on total consumption of every kind of energy by path analysis, and then consider establishing a Structural Vector Autoregression model of energy conservation and emission reduction in three statuses. Research shows that if the international oil price increases by 1%, the energy consumption per GDP and carbon dioxide emission increase by 0.092% and 0.053% respectively in the corresponding period. In the status of high energy consumption and high emission, if the international oil price increases by 1%, the energy consumption per GDP and carbon dioxide emission increase by 0.043% and 0.065% respectively in the corresponding period. In the status of low energy consumption and low emission, if the international oil price increases by 1%, the energy consumption per GDP per unit increases by 0.067% and carbon dioxide emission decreases by 0.085% in the corresponding period.

Natural gas has become more and more important in the world energy market with the change of energy consumption structure and consumption subjects. This paper applies the panel smooth transition regression (PSTR) model to study the nonlinear relationship between natural gas consumption and economic variables of emerging economies, and the empirical results show that: (1) There is a non-linear relationship among natural gas consumption, GDP per capita, industrialization and urbanization rate; (2) The optimal PSTR model is a two-regime model by using the lagged industrialization as a transition variable, and the impact of GDP per capita and of industrialization on natural gas consumption shows incomplete symmetry in low and high regime, respectively; (3) The result of time-varying elasticity analysis indicates that natural gas consumption is inelastic to GDP per capita, but elastic to both industrialization and urbanization. The elasticity of GDP per capita generally decrease with fluctuation, the elasticity of industrialization tends to rise, and the elasticity of urbanization is linear at high level; (4) Regional difference shows that there are 10 emerging economies are in first regime (below industrialization of 43.2%), and the remaining 6 are in second regime. This provides reference for countries in different transformation periods to make economic policies adapting to energy saving, energy structure optimization and other sustainable development strategies.

Currently, oversupply coal and coal-based power in China poses a great challenge to energy structure optimization and emissions reduction. The energy industry, however, is closely linked to the financial sector. In view of this, using a non-linear Panel Smooth Transition Regression (PSTR) model, this paper examines the threshold effects of financial developments on energy supply structures for 17 energy supply provinces in China observed over 2000–2014. The main results are: (1) The ratio of coal supply (LCSR) specification is seen to be a four-regime PSTR model with added value in the financial industry/GDP (LFIR) as the threshold variable. The LFIR and LCSR show a positive correlation, and the elastic coefficients change between 0.02 and ~0.085; the impact of financial institutions’ loan balance/GDP (LLAN) on LCSR takes on an inverse U-shaped curve: first positive, then negative, and again positive with the financial crisis in 2008 as the turning point; (2) The ratio of thermal power generation (LTPG) specification is seen to be a two-regime PSTR model with investment in the coal industry/GDP (LCIR) as the threshold variable. Results show that LFIR has a negative effect on LTPG, and the coefficients in the low regime tend to be 0.344%, then gradually decrease to 0.051% in the high regime. The influence of LLAN on the LTPG is positive before and negative after the financial crisis. The influence of the foreign direct investment GDP proportion (LFDI, the degree of financial openness) on the LCSR and LTPG both remain negative. Therefore, in the process of formulating energy conservation policies and adjusting energy-intensive industrial structures, the government should fully consider the effect of financial developments.

This paper is aimed to make sense of the real effect of implement of social healthcare insurance on one’s medical expense in China. Due to previous studies drew various and inconsistent conclusions on this issue, this works intend to apply meta-analysis to the problem. For 31 related studies, we first implement an advanced conditional Dirichlet-based Bayesian semi-parametric model specific to meta-analysis, and come to a primary conclusion that healthcare possesses little probability reducing one’s medical expense in China. Further, the authors conduct random effects meta-regression and find that heterogeneity exists among the observed effect sizes. Mixed effects model shows that the age variation may is actually the heterogeneity source. The coefficients for Non-old and Old are respectively 0.29 and 0.54, implying that when researching on the medical expense for the elderly, it is more likely to conclude the medical insurance could increase medical spending. The coefficients for IV and OLS are both remarkably negative at 90% confidence level. This suggests when directly using Instrument Variable (IV) approach and OLS method to assess the implementation effect for the healthcare insurance, it is inclined to result in the reduced impact on medical expense. We deduce this is because this two methods can’t solve the sample-selection bias when compared with the Two-part model and difference-in-difference (DID) model. Based on the results and discussion, we finally propose suggests for the government.

In recent years, it has been a hot pot to explore the effectiveness of basic medical insurance. However, due to different sample characteristics, time series length, models and so on used by authors, there exists big difference among relevant papers. In this paper, we try to apply meta regression analysis (MRA, a prevalent statistic literature review method) to explore its influence on family expenditure, and 90 sample observations were extracted from 49 important literatures. We find: 1) All the index construction, sample characteristic, model selection, control factors will influence the conclusions of medical insurance effectiveness; 2) The implement of basic medical insurance will increase household consumption other than the new rural cooperative systems; 3) The implement of basic health insurance has not really reduce family’s medical expense. Thus, we induce that adverse selection exists in China’s medical insurance.