Constructing segmented rental housing indices: evidence from Beijing, China

Abstract

PurposeThis paper aims to construct rental housing indices and identify market segmentation for more effective property-management strategies.Design/methodology/approachThe hedonic model was employed to construct the rental indices. Using the k-means++ and REDCAP (Regionalisation with Dynamically Constrained Agglomerative Clustering and Partitioning) approaches, the authors conducted clustering analysis and identified different market segmentation. The empirical study relied on the database of 80,212 actual rental transactions in Beijing, China, spanning 2016–2018.FindingsRental housing market segmentation may distribute across administrative boundaries. Properly segmented indices could provide a better account for the heterogeneity and spatial continuity of rental housing and as well be crucial for effective property management.Research limitations/implicationsResidential rent might not only vary over space but also interplays with housing price. It would be worth studying how the rental market functions together with the owner-occupied sector in the future.Practical implicationsResidential rental indices are of great importance for policymakers to be able to evaluate housing policies and for property managers to implement competitive strategies in the rental market. Their constructions largely depend on the analysis of market segmentation, a trade-off between housing spatial heterogeneity and continuity.Originality/valueThis paper fills the gap in knowledge concerning segmented rental indices construction, particularly in China. The spatial constrained clustering approach (REDCAP) was also initially introduced to identify regionalised market segmentation due to its superior performance.