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Stochastic models for strategic resource allocation in nonprofit foreclosed housing acquisitions

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  • Bayram, Armagan
  • Solak, Senay
  • Johnson, Michael
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    Abstract

    Increased rates of mortgage foreclosures in the U.S. have had devastating social and economic impacts during and after the 2008 financial crisis. As part of the response to this problem, nonprofit organizations such as community development corporations (CDCs) have been trying to mitigate the negative impacts of mortgage foreclosures by acquiring and redeveloping foreclosed properties. We consider the strategic resource allocation decisions for these organizations which involve budget allocations to different neighborhoods under cost and return uncertainty. Based on interactions with a CDC, we develop stochastic integer programming based frameworks for this decision problem, and assess the practical value of the models by using real-world data. Both policy-related and computational analyses are performed, and several insights such as the trade-offs between different objectives, and the efficiency of different solution approaches are presented.

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    Bibliographic Info

    Article provided by Elsevier in its journal European Journal of Operational Research.

    Volume (Year): 233 (2014)
    Issue (Month): 1 ()
    Pages: 246-262

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    Handle: RePEc:eee:ejores:v:233:y:2014:i:1:p:246-262

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    Web page: http://www.elsevier.com/locate/eor

    Related research

    Keywords: OR in societal problem analysis; OR in strategic planning; Foreclosures; Stochastic programming; Resource allocation;

    References

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    1. John Y. Campbell & Stefano Giglio & Parag Pathak, 2009. "Forced Sales and House Prices," NBER Working Papers 14866, National Bureau of Economic Research, Inc.
    2. Rui Yao, 2005. "Optimal Consumption and Portfolio Choices with Risky Housing and Borrowing Constraints," Review of Financial Studies, Society for Financial Studies, vol. 18(1), pages 197-239.
    3. Schuetz, Jenny & Been, Vicki & Ellen, Ingrid Gould, 2008. "Neighborhood effects of concentrated mortgage foreclosures," Journal of Housing Economics, Elsevier, vol. 17(4), pages 306-319, December.
    4. Johnson, Michael P. & Solak, Senay & Drew, Rachel Bogardus & Keisler, Jeffrey, 2013. "Property value impacts of foreclosed housing acquisitions under uncertainty," Socio-Economic Planning Sciences, Elsevier, vol. 47(4), pages 292-308.
    5. Medaglia, Andres L. & Graves, Samuel B. & Ringuest, Jeffrey L., 2007. "A multiobjective evolutionary approach for linearly constrained project selection under uncertainty," European Journal of Operational Research, Elsevier, vol. 179(3), pages 869-894, June.
    6. Chalabi, Zaid & Epstein, David & McKenna, Claire & Claxton, Karl, 2008. "Uncertainty and value of information when allocating resources within and between healthcare programmes," European Journal of Operational Research, Elsevier, vol. 191(2), pages 530-539, December.
    7. Christoph H. Loch & Stylianos Kavadias, 2002. "Dynamic Portfolio Selection of NPD Programs Using Marginal Returns," Management Science, INFORMS, vol. 48(10), pages 1227-1241, October.
    8. Harding, John P. & Rosenblatt, Eric & Yao, Vincent W., 2009. "The contagion effect of foreclosed properties," Journal of Urban Economics, Elsevier, vol. 66(3), pages 164-178, November.
    9. Solak, Senay & Clarke, John-Paul B. & Johnson, Ellis L. & Barnes, Earl R., 2010. "Optimization of R&D project portfolios under endogenous uncertainty," European Journal of Operational Research, Elsevier, vol. 207(1), pages 420-433, November.
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