The Capitalization of School Quality in Rents in the Beijing Housing Market: A Propensity Score Matching Method

Abstract

In China, the capitalization of education resources in housing prices has been widely discussed. However, insufficient attention is paid to it in rents. Thus, this paper mainly aims to identify the capitalization of school quality in rents. It estimates a hedonic treatment effects model by introducing the propensity score matching (PSM) method. The empirical analysis is based on 49,438 rental transaction data of 2016–2018 in Beijing, China. It finds that school quality can be significantly capitalized in rents across different school quality (ranked as 1st-class, 2nd-class, and popular-class), space, and time. Besides, quality school density (the number of quality schools) within neighborhoods can significantly moderate the nearest school’s capitalization, promoting a 3.5% capitalization increase in outer municipal districts but a 3% decrease in inner districts. The popular-class schools can be capitalized into the rent of inner districts, probably because of other exogenous factors (e.g., housing prices, public transit). In addition, the equitable housing policy might show a potential risk in worsening social inequality between homeowners and renters in the municipal areas with high competition for 1st-class schools. In contrast, it may remedy such inequality in outer districts with less competition for quality schools.

Effects of the Olympic Announcement and the Actual Event on Property Values: The Case of the 2018 PyeongChang Winter Olympic Games

“…We used variables that are likely to determine housing prices, which include unit-specific features (unit size and floor and the number of bedrooms and bathrooms), apartment-complex-specific features (age, the number of units, floor area ratio, building coverage, parking spaces, and distance to the closest hospital and school), and city-specific features (city population, GRDP, and crime rates). Following Song [40], we use one-to-one nearest neighbor matching for each unit in Gangneung with a replacement.…”

“…After applying propensity score matching, a difference-in-difference approach was used to estimate the treatment effect with the 2010-2012 sample. Since a hedonic price model was used for analyzing housing prices [21,28,40], we modified the hedonic price model as follows:…”

How Does the Quality of Junior High Schools Affect Housing Prices? A Quasi-Natural Experiment Based on the Admission Reform in Chengdu, China

“…In addition, although we collected enough housing transaction records this time, data accessibility issues may occur in the future, which will hinder us from using the parallel trend test to ensure the robustness of the DID results. Given that, the propensity score matching (PSM) method may also be helpful, since it usually has lower requirements regarding the amount of data [68]. Therefore, we could improve the DID method with the PSM method if we had short panel data.…”