Chinese government policy officially identify the Yangtze River Economic Belt (YREB) as one of regional green development strategies firstly in 2014. This strategy can be regarded as quasi-natural experiment, this paper aims to test its impact on regional environmental total factor productivity (TFP). First, slack-based measure model is used to calculate the environmental TFP from 2005 to 2017 at provincial level. Second, based on Chinese official statistics, differences-in-differences (DID) method is applied to construct an evaluation model of policy effect, combining with the kernel matching in propensity score matching (PSM) method. The results show that environmental TFP of YREB has significant spatial differences, with characteristic of high-east and low-west, its average level is 11.69 percentage points higher than the national average. YREB strategy promotes regional economic growth, but it does no effect on the regional environmental TFP yet. Modelling suggests that YREB strategy may play a role in the short term. From the significance of the control variables, infrastructure construction level is positively correlated with environmental TFP, while per capita GDP, financial development and energy consumption intensity have negative effect on environmental TFP. Based on this, policymakers should focus on green development, promoting industrial transformation, and enhancing environmental protection.

The development of new energy in developing areas should not only consider the effect on local economic growth, but also give some attention to its spillover effect for economic growth in neighboring areas and take a new path of cluster-style development and cooperative governance. On the basis of Moran’s I and the Spatial Dubin Model (SDM), this paper analyzes the spatial spillover effect of new energy development on economic growth of 21 developing areas in China from 2000 to 2017. The results show that: (1) According to the Moran’s I, there are significant economic agglomeration characteristics in the spatial distributions among different areas in the study area. (2) A comparative study using the mixed Ordinary Least Squares (OLS) method and SDM shows that new energy has a negative spillover effect on the economic growth of neighboring areas when considering spatial factors, but this negative effect is underestimated in the mixed OLS method. (3) In addition to the core explanatory variable, the spatial spillover effect of new energy on economic growth is also affected by control variables, but the degree of impact varies. The results imply that some effective policy measures, such as sustainable development mechanisms, industrial distribution, and comparative innovation, should be taken to encourage new energy development for the high quality growth in developing areas on the national, regional, and global scale.