Urban green vegetation provides amenity value for urban residents and improves the living environment. These changes in value can be reflected in the variation of house prices. This paper uses a unique housing transaction data set to estimate the impact of urban green vegetation on house values in Beijing, China, using the hedonic price model. To measure urban green vegetation, we calculated the normalized difference vegetation index (NDVI) by time-series Landsat TM 8 remote-sensing imagery. For model specification, we applied spatial lag models to address spatial spillover effects that might lead to biased estimates if ignored. Spatial hedonic results indicate that urban green vegetation has a positive effect on residential housing prices when the measurement scale of NDVI value is smaller than or equal to 18.01 acres for each block of flats, whereas greater NDVI values generate a negative effect on property values if the scale is larger. This implies that urban green vegetation within 135 m could increase house prices in the range of 7.95–10.59%, which indicates a potential 20.2–26.9 billion yuan increase in the value of the sample real estate market in Beijing.

Global climate problems caused by the overuse of fossil energy need to be settled urgently. To solve global warming threatening human life and production, environmental control policies have been proposed as the mainstream ways to push renewable energy development worldwide, such as carbon tax, carbon trading, emissions trading, and fiscal subsidies. This study examines how carbon tax and carbon emission trading policies could be coupled with subsidy policies to better promote renewable energy development. The data come from seven carbon emission trading pilots from 2013 to 2017 in China. Based on the evolutionary game, the research simulates the onshore wind power investment to deeply explore the spontaneous evolution process. Considering carbon tax and carbon emission trading policies, the two evolutionary game models are constructed under the context of fiscal subsidy policy, respectively. The results show that, under the scenario of carbon trading and subsidy policy coordination, investors will vote for wind farms and under the scenario of the carbon tax and subsidies coordination, investors will pay the funds in coal-fired power generation. Besides, this is worth noting that excessive carbon tax may give rise to the shrinking of the power industry. Accordingly, it is suggested that the government should continue to implement the carbon emission trading policy and maintain the free quota below 80% and the carbon emission trading price above 120.02 yuan/ton.