The housing sales market in China has flourished and gained considerable interest, while the housing rental market has lagged behind and been ignored over the past two decades. With the acceleration of urbanization, the housing rental demand is rising rapidly. Exploring and comparing the influencing factors on housing sale prices and rental prices has significance for sustainable urban planning and management. Using house purchase transaction and rent transaction data in 2017, as well as the average housing price and rent data in 2016 in Beijing, China, this paper compares the spatial distribution and it employs the hedonic price model and quantile regression model to quantify the average and distributional effects of micro-level influencing factors on housing prices and housing rents. Results show that housing prices and housing rents both have a decentralized distribution with multiple centers, but rents of residential communities with high housing prices may not necessarily be high. Both homeowners and renters prefer properties with good structural, locational, and neighborhood characteristics, as well as a good school attendance zone, whereas they still differ in terms of preferences. Homeowners prefer a higher-quality living environment. Renters are more concerned with proximity to an employment center and public transit convenience. Moreover, the price premium of school quality for homeowners exceeds the premium for renters. Higher-priced homeowners or renters differ in the preferences from lower-priced homeowners or renters. Higher-priced homeowners and higher-priced renters are more willing to live in property with a larger number of bedrooms, proximity to a major employment center, park, or school, as well as a location in a school attendance zone with higher school quality.

Rapid expansion in Mongolia has resulted in an inequality in livelihood, growing air pollution, and unevenly distributed social goods, which implies that the urbanization of Mongolia is experiencing a chronic imbalance. Using 21 Aimags and 1 capital in Mongolia as the research object, this paper provides a detailed assessment of the coupling coordination degree (CCD) to analyze the coupling and coordination relationship between urbanization and urban residents’ livelihood level. The results suggest that there is a serious imbalance in the coordination of urban development and urban residents’ livelihood among the Aimags of Mongolia. The high CCD values were mainly concentrated in the central regions of Mongolia, while the low values were clustered in the western and eastern areas. The spatial Durbin model was employed to analyze the driving forces of the CCD, and the results imply that the secondary industry share and the number of registered enterprises play significant roles in promoting coordination between urbanization and urban residents’ livelihood level. Here, we present an overview of how our analysis can provide useful insights for policymakers and decision makers.