Duration of Residence in the Rental Housing Market

Abstract

This paper estimates a proportional hazard model of duration of residence in rental housing. The study employs unique data from the BLS-CPI housing sample to construct the duration of rental occupancy for metropolitan areas over the 1987-1998 period. American Housing Survey and other metropolitan economic data are used to proxy time-varying covariates of duration of residence. The paper employs an innovative semi-parametric estimation approach for group duration analysis of the proportional hazard model, as originally proposed by Ryu (1994) and then modified by Deng [(1995), (1997)]. Results of the analysis indicate that the duration of residence in rental housing varies significantly across individual units and market segments. In fact, the duration of residence is highly time dependent, given significant intertemporal variation in many of the housing and market covariates. The paper provides evidence of high tenant turnover rates at about 3 years of residence. However, the turnover hazard curve depends as well on market conditions and housing policy. For example, imposition of rent control can shift the peak of the tenant turnover hazard curve to the left. Research findings further indicate that median housing costs, public housing share of the rental stock, poverty rate, and African-American and Hispanic share of tenant households are among those factors that positively affect tenant turnover hazard rates and hence are negatively related to tenant residence duration. Elevator buildings, unemployment rate, population growth and central city share of the rental stock negatively affect tenant turnover hazard rates and hence are positively related with tenant residence duration. Further, the estimated pattern of duration of residence was shown to vary substantially across 33 large metropolitan markets. Simulation results further indicate the sensitivity of duration of residence to housing locational and structural characteristics. For example, findings for New York City indicate that increased geographic dispersion of rental housing, as reflected in a reduction in the share of rental stock in the central city to national average levels, would serve to boost cumulative tenant turnover rates by 12 percent by the end of year three of the rental lease. Similarly, simulated reduction in the density of rental housing, as reflected in downward adjustment in the share of NYC buildings with seven or more stories to that of the national average level, would serve to increase cumulative tenant turnover rates by 13 percent. The research provides new evidence as regards tenant and market characteristics that determine the duration of residency. Clearly, an improved understanding thereof offers new insights as regards fluctuations in tenant turnover, building occupancy, and rent flows, as well as new confidence in pro forma assumptions critical to rental housing development.

Institutional investors

“…Growth over the last two decades in the seniors housing and care industry has resulted in size and market capitalization levels that warrant the attention of large investors (NIC, Size 1999 housing sector where a recent study showed that 46% of the tenants in apartments with elevators stayed less than one year and 37% of the residents in apartments with no elevator left within one year (Deng 2003).…”

Housing sales in urban Beijing

“…There are some paper adopting survival or duration models in housing, mostly focusing on USA mortgage market (Vandell et al, 1993;2001;Ciochetti et al, 2003a,b;Lacour-Little and Malpezzi, 2003;Foote, Gerardi and Willen, 2008;Kau, Keenan and Li, 2011) or duration of rental vacancies in USA (Sternberg, 1994;Gabriel and Nothaft, 2001;Deng, Gabriel and Nothaft, 2003;Archer, Ling and Smith, 2010); moreover, the timing of land development in USA was also analysed (Cunningham, 2006). Papers outside USA include Bulan, Mayer andSomerville (2009) in Canada, Feijten andMulder (2010) in the Netherlands, and Ström (2010) Adopting a time framework to analyse survival models in housing, Vandell et al (1993) analyse individual commercial mortgage default with data from a major multi-line USA insurance company.…”

Ownership Duration in the Residential Housing Market: The Influence of Structure, Tenure, Household and Neighborhood Factors

“…The effect on housing turnover from property tax protection through California's Proposition 13 has been measured by Wasi and White (2005). Another line of research focuses on duration of rental occupancy, but does not treat duration of the underlying unit ownership (Deng et al 2003;Gabriel and Nothaft 2001). A focus of the Gabriel and Nothaft (2001) analysis was the effect of duration of residential vacancies on equilibrium vacancy rates.…”

“…This condition is typically not met by economic data, which are most often gathered periodically in discrete time intervals. Thus, an augmentation of the model, similar to that employed by Deng et al (2003), is required. The sales observations utilized in this analysis include the day the sale occurred, thus; the data accommodates the requirement for continuity.…”