Date of Award:

5-2006

Document Type:

Thesis

Degree Name:

Master of Science (MS)

Department:

Human Development and Family Studies

Department name when degree awarded

Family, Consumer, and Human Development

Committee Chair(s)

Yoon G. Lee

Committee

Yoon G. Lee

Committee

Jean Lown

Committee

Tory Beckert

Abstract

By using data from the 1995 Property Owners and Managers Survey (POMS), this study explores the role of owner characteristics (socioeconomic and behavioral) and ownership characteristics in predicting the likelihood of using multifamily property for retirement purposes. In addition, this study examines the likelihood of reporting a profit in the prior year among those who purchase multifamily properties for retirement purposes. The sample consists of property owners who own multifamily real estate other than their primary residence (N = I ,3 19). Property owners with retirement savings motive (RSM) were more likely to be male, White, have income more than $100,000, own more than 30 units, and be located in the Midwest. Property owners who reported a profit in the prior year were more likely to be male, White, own property more than 10 years, own 30 or more units, and be located in the Midwest.

The results of logistic regression analysis indicate that gender, income, the amount of time contributed to maintenance by the owner, owner living at the property, individual ownership, and the number of units in the property were significantly related to the likelihood of owning real estate for retirement purposes. Being older, White, having higher income, contributing to maintenance, being an individual owner, owning the property for more than 10 years, and owning more than live units were significantly related to the likelihood of reporting a profit in the prior year.

By identifying who is purchasing multifamily properties for retirement purposes and their likelihood of success, educators, researchers, financial planners, and economists can gain a better understanding of the multifamily housing market. Individual investors, financial planners, lenders, and researchers can utilize this information to expand, develop, or reline models that measure the quality of a financial deal (i.e., the probability of making a profit and/or risk of default).

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