Investigating the effects of service and management on multifamily rents: a multilevel linear model approach

Abstract

Unlike the large body of research on the determinants of single family prices and rents, the determinants of multifamily rents has received much less exploration. Using a recent and comprehensive micro-level dataset of multifamily housing units in Montgomery County, Maryland, USA, we applied a multilevel linear model with random coefficient to explore the determinants of multifamily rents, including the effects of service and management attributes. The findings are as follows: (1) first we find that a multilevel linear model is better suited to address datasets that include multiple apartment units in a smaller set of facilities, (2) for certain datasets—including ours–a random coefficients model outperforms both an OLS and random intercept model and (3) the effects of service and management variables on multifamily rents vary across types of service and management. Pet allowance, availability of short-term leasing options, and storage service availability increase rents significantly. Conversely, offering units to property employees and services to those with a disability decrease rents significantly.