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Duration of Residence in the Rental Housing Market

Yongheng Deng, Stuart A. Gabriel and Frank E. Nothaft.
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.