This thesis studies the impact of dockless bike-sharing (DBS) on subway proximity premiums that were observed via housing market. To find out the aggregated effect of DBS on subway proximity premiums, we apply hedonic price analysis with OLS and S2SLS estimates using data scraped from a Chinese real estate agent and Baidu Map. Results show that apartments within 3km to subway stations have a price premium of 2.25% per km (1.42% with S2SLS estimates) on average, and the entry of DBS raises subway proximity premiums throughout the two-year period (2015-2017). Quantile regression is then used to quantify variations across pre-defined market segments. We find that the entry of DBS significantly raises the premium in low-end houses. A difference-in-difference (DID) approach is employed to identify the effects of DBS by month. We find that the market starts to respond in one month after the entry of Mobike. Instead of raising the premium, the entry of DBS attenuates price premiums in the first four months. After the four-month period, there is no indication of DBS’s effect on subway proximity premiums.