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Abstract: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.

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 Nonold 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 National Center for Mathematics and Interdisciplinary Sciences, CAS, Beijing, China 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.