Forecasting Seniors Housing Demand in Florida

David Macpherson and Stacy Sirmans

Journal of Real Estate Portfolio Management, 1999, vol. 5, issue 3, 259-274

Abstract: Executive Summary. This study uses a multinomial logit model to estimate the demand for seniors housing in Florida using these categories of housing choices: (1) no care required, owner-occupied; (2) no care required, renter-occupied; (3) assisted living; (4) congregate care; and (5) nursing home. The logit results are combined with the United States Census population projections to forecast the demand for the housing categories through the year 2025. Some results are: The no care, owner-occupied category is the largest. The population in assisted living is predicted to grow by 149% from 1990 to 2025. Congregate care is the smallest category and is predicted to remain so. Older non-minorities are more likely to use congregate care while minorities have a very low probability. No care, renter-occupied is the second largest category and is predicted to grow at the highest annual rate. These changes in demand for seniors housing have implications concerning reallocation of resources to meet the specific seniors housing needs.

Date: 1999
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/10835547.1999.12089587 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:repmxx:v:5:y:1999:i:3:p:259-274

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/repm20

DOI: 10.1080/10835547.1999.12089587

Access Statistics for this article

Journal of Real Estate Portfolio Management is currently edited by Peng Liu and Vivek Sah

More articles in Journal of Real Estate Portfolio Management from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().