The Impact Of Urban Parks On Residential Price In The Main Urban Area Of ​​Kunming City

With the development of the socio-economic, residents are paying more attention to the quality of the living environment. Beautiful landscapes can make people relax themselves and also good for people’s health. As public properties, city parks have the features of scarcity. The closer the residence community with the city parks, the residents benefit more public welfare. The housing prices will get higher. On the other hand, the value of city parks is recessive, it’s difficult to measure the economic benefit directly in currency. So, it’s often neglected and lead to a Public financial loss.This paper attempts to explore the impact of city parks on housing price from levels of housing and residential community. What’s more,the spatial autocorrelation effect of housing price in Kunming is also analyzed in this paper. The conclusions of this paper are as follows:(1) This paper chose Cuihu park, Guilonghu park and Yueyatan park, using Kriging interpolation techniques to see the trend of housing price. The park as the center, the housing price declined around the park. Cuihu park is most obvous, Yueyatan park pond, followed by Guilonghu park again.(2) The empirical result shows that there is an inverse relationship between the housing price and its distance from the park while the park size is positively correlated to the house price. For the standard house, distance to the nearest park for each additional 100 meters, housing prices fell 21.168 thousand yuan, while the area of the recent increase per 1 hectare park, home prices will increase 7.6145 thousand yuan.(3) The Park has the concept of the largest service radius, the impact of the park on housing prices is not necessarily infinity. This paper assumes that each additional 50 meters distance, the standard residential prices fell less than 0.25%, the park has no effect on housing prices. So, we believe that, the distance of impacts of the park on housing price is about 1898.2 meters.(4) As can be seen from the Moran’s I index and LISA map, Kunming residential housing price has strong spatial autocorrelation. Impact on housing prices hedonic price model makes use of the general urban park landscape features variable is magnified, we use spatial lag model correction. Empirical results show that the spatial econometric model superior than the average hedonic price model has better explanatory power. Consider Spatial autocorrelation effect, Kunming City Park on housing prices are still very huge impact.