Abstract
Community development corporations seek to stabilize neighborhoods affected by the recent foreclosure crisis through acquisition and redevelopment of distressed properties. One rationale for this work is the alleviation or avoidance of negative foreclosure impacts. We estimate the lost value to proximate properties associated with a single foreclosure through a Markov chain representing probabilistic transitions between foreclosure stages. We apply our model to a case study of foreclosure properties in Chelsea, MA. A rank ordering by estimated property value impacts indicates significant potential gains in social value as compared to current community development practice. We extend our basic model to address the effects of clusters of foreclosed units upon the value of proximate properties. This study provides additional support for the use of decision modeling in foreclosed housing acquisition and redevelopment.
| Original language | English |
|---|---|
| Pages (from-to) | 292-308 |
| Number of pages | 17 |
| Journal | Socio-Economic Planning Sciences |
| Volume | 47 |
| Issue number | 4 |
| DOIs | |
| State | Published - Dec 2013 |
ASJC Scopus Subject Areas
- Geography, Planning and Development
- Economics and Econometrics
- Strategy and Management
- Statistics, Probability and Uncertainty
- Management Science and Operations Research
Keywords
- Community development
- Decision models
- Foreclosed housing
- Markov chains
- Policy analysis
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