In recent years, the Chinese real estate market has developed rapidly. Although its growth promotes the economic boom in China, many underlying problems exist with such a fast expansion. House prices with such an enormous increase have already outpaced household affordability. What's more, the problematic structure of Chinese real estate will be harmful to the stabilization of the Chinese economy. Therefore, the government has implemented a number of policies to regulate the housing market, but the results have not been what the central government expected. The problems of the Chinese real estate market are very complex. The uneven development of Chinese cities will weaken the effect of national macro control policies. What's more, the land supply is controlled by the government, and local governments rely on land sales to reduce budget deficits. In order to have a clear insight of the determinants of the Chinese real estate market, several attempts have been taken in my study. The analyses are conducted using panel data of Chinese representative cities over the time period from 1999 to 2014. Because of the regional variation of China, three estimation models are set up corresponding to first-tier, second-tier and third-tier cities. In addition, a national model serves as a benchmark. In order to ensure that the estimation results are reasonable, co-integration has been tested between house prices and their impact factors as well. From the theoretical and empirical analyses, I have found that the major influencers of house prices in first-tier cities are income, positive anticipation of house prices rising and land prices. These three factors also significantly affect house prices in second-tier cities, which are very similar to the first-tier cities. However, the impact factors of house prices in third-tier cities not only include income but also contain local government's interference. In order to maintain a healthy development of the Chinese real estate market, proper suggestions are put forward based on the findings of this research. Keywords: house price, income, land prices, panel data, first-tier cities, second-tier cities, third-tier cities