Multifamily Housing: A Review of Theory and Evidence

The growing importance of multifamily housing as a viable choice of residence is evidenced by the number of empirical and theoretical studies in real estate literature. Researchers have investigated the role of this sector of the real estate market for decades. This survey article examines more than one hundred studies and categorizes them into five groups: economic and market efficiency issues; property valuation and appraisal issues; regulatory, zoning, and clustering of multifamily complexes; costs, returns, and rental income issues; and demand, vacancy, and occupancy issues. This study seeks to provide a concise, categorical presentation of findings on issues related to the environment and performance of multifamily housing.

Anticipating Change in Development Activity Levels

This study demonstrates how cointegration analysis of privately-owned housing within disparate areas of the United States can aid developers in anticipating changes in the level of market activity. The study analyzes change in the number of housing units within four geographic regions: the Northeast, the Midwest, the South and the West. Whereas most studies of regional variation in real estate activity have focused on short-run analysis, this research extends the examination to consider the impact of exogenous variables over a longer time frame. The study uses Citibase data from 1959 through 1995. Results indicate that the four regions move together in the long run and are driven by one common factor, but that change in the South and the West lead those in the other two regions. Results have widespread policy implications for residential and commercial developers nationwide, because change within the dominant areas may serve as indicators of developing change elsewhere.

Security Measures and the Apartment Market

This paper examines the effect of security measures on apartment rent and occupancy. Three variables representing various security measures are estimated in a simultaneous model of rent and occupancy. Providing 24 hour security has a significant positive effect on both rent and occupancy. Having a manager living on site or a manned front desk/restricted entry does not significantly affect rent. All three variables, however, have a significant positive effect on occupancy. It would appear that, although landlords cannot extract higher rents for some security measures, all three measures included in this study act to increase occupancy.

Determinants of House Prices: A Quantile Regression Approach

Hedonic price function, Quantile regression, Spatial lag, R31, C21, C29,

The Value of Housing Characteristics: A Meta Analysis

This paper provides a meta regression analysis of the nine housing characteristics that are appear most often in hedonic pricing models for single-family housing: square footage, lot size, age, bedrooms, bathrooms, garage, swimming pool, fireplace, and air conditioning. Meta regression analysis is useful for comparing the estimated regression coefficients from different studies. The goal in this study is to determine if the estimated coefficients vary by geographical location, time, type of data, and model specification. The results show that the estimated coefficients for some characteristics vary significantly by geographical location. These include square footage, lot size, age, bathrooms, swimming pool, and air conditioning. Controlling for time shows that the effects of these housing characteristics on house price have not changed over time. Controlling for type of data produces differences in coefficients for bathrooms. Controlling for wealth as measured by median household income has no significant impact on the coefficients for the housing characteristics. If the study controlled for square footage, the coefficients for lot size decrease. Controlling for the size of the hedonic model affects the coefficient for square footage. Copyright Springer Science + Business Media, LLC 2006Selling price, Time on the market, Meta regression, Moderator variables, Hedonic models,