Evaluating drivers of housing vacancy: a longitudinal analysis of large US cities from 1960 to 2010
- 주제(키워드) Urban regeneration , Housing vacancies , Vacant land , Longitudinal analysis , Regression
- 주제(기타) Environmental Studies
- 주제(기타) Regional & Urban Planning
- 주제(기타) Urban Studies
- 등재 SSCI, SCOPUS
- OA유형 Green Accepted
- 발행기관 SPRINGER
- 발행년도 2019
- URI http://www.dcollection.net/handler/ewha/000000161422
- 본문언어 영어
- Published As http://dx.doi.org/10.1007/s10901-019-09684-w
- PubMed https://pubmed.ncbi.nlm.nih.gov/31857804
초록/요약
Housing vacancies have become a major issue in depopulating, or shrinking, cities. All urban areas, however, are subject to some degree of vacant housing. A small percentage is necessary to allow mobility and sufficient space for growth, and is an indicator of healthy urbanization. Conversely, widespread housing vacancies may indicate structural crisis due to property abandonment. Land area and population changes, shifts in employment, demographic trends, development intensity, and economic conditions are primary drivers of housing vacancies. The degree to which these interrelated factors contribute can fluctuate by city. This paper explores relationships between factors contributing to housing vacancies over time to identify changes in underlying factors. The research examines U.S. cities of over 100,000 population over the period of 1960-2010, conducting multivariate regression analyses in 10-year periods and performing longitudinal panel analyses. The regressions examine changes in urban housing vacancy factors over time while the panel models assess which factors have remained consistent. The panel model results indicate that population change, percent nonwhite populations, unemployment and density are consistent, significant predictors of housing vacancies, The incremental regression models suggest that unemployment and regional location have also been strong indicators of housing vacancies. These results, while somewhat exploratory, provide insight into long-term data that cities should track over time to determine the optimal policy approaches to offset housing vacancies.
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