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Determining the impact of low-cost housing development on nearby property prices using discrete choice analysis

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  • M. Du Preez
  • M.C. Sale
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    Abstract

    This paper presents an application of the conditional logit model to a small, Nelson Mandela Bay neighbourhood housing data set, with the objective of determining the impact of proximity to a low-cost housing development on nearby property prices. The results of this pilot study show that the average household in the neighbourhood of Walmer is willing to pay between R27 262 and R195 564 to be located 86m further away from an existing low—cost housing development. In addition to this, the probability of choosing a specific house increases if the house has a swimming pool, an electric fence, the lower its price and the closer it is to the nearest school.

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    File URL: http://econrsa.org/home/index.php?option=com_docman&task=doc_download&gid=402&Itemid=67
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    Bibliographic Info

    Paper provided by Economic Research Southern Africa in its series Working Papers with number 265.

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    Length: 13 pages
    Date of creation: 2012
    Date of revision:
    Handle: RePEc:rza:wpaper:265

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    1. Earnhart, Dietrich, 2002. "Combining Revealed and Stated Data to Examine Housing Decisions Using Discrete Choice Analysis," Journal of Urban Economics, Elsevier, vol. 51(1), pages 143-169, January.
    2. Patrick Bayer & Robert McMillan & Kim Rueben, 2004. "Residential Segregation in General Equilibrium," Working Papers 885, Economic Growth Center, Yale University.
    3. Quigley, John M., 2006. "Urban Economics," Berkeley Program on Housing and Urban Policy, Working Paper Series qt0jr0p2tk, Berkeley Program on Housing and Urban Policy.
    4. Nechyba, Thomas J. & Strauss, Robert P., 1998. "Community choice and local public services: A discrete choice approach," Regional Science and Urban Economics, Elsevier, vol. 28(1), pages 51-73, January.
    5. George R. Parsons & Mary Jo Kealy, 1992. "Randomly Drawn Opportunity Sets in a Random Utility Model of Lake Recreation," Land Economics, University of Wisconsin Press, vol. 68(1), pages 93-106.
    6. Lyons, Robert F. & Loveridge, Scott, 1993. "An Hedonic Estimation Of The Effect Of Federally Subsidized Housing On Nearby Residential Property Values," Staff Papers 13377, University of Minnesota, Department of Applied Economics.
    7. Donald C. Guy & John L. Hysom & Stephen R. Ruth, 1985. "The Effect of Subsidized Housing on Values of Adjacent Housing," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 13(4), pages 378-387.
    8. Patrick Bajari & Matthew E. Kahn, . "Why Do Blacks Live in The Cities and Whites Live in the Suburbs?," Working Papers 00007, Stanford University, Department of Economics.
    9. Bartik, Timothy J. & Smith, V. Kerry, 1987. "Urban amenities and public policy," Handbook of Regional and Urban Economics, in: E. S. Mills (ed.), Handbook of Regional and Urban Economics, edition 1, volume 2, chapter 31, pages 1207-1254 Elsevier.
    10. Bulent Uyar & Kenneth H. Brown, 2005. "Impact of Local Public Services and Taxes on Dwelling Choice within a Single Taxing Jurisdiction: A Discrete Choice Model," Journal of Real Estate Research, American Real Estate Society, vol. 27(4), pages 427-444.
    11. Raymond B. Palmquist & Adis Israngkura, 1999. "Valuing Air Quality With Hedonic and Discrete Choice Models," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 81(5), pages 1128-1133.
    12. John M. Quigley, 1976. "Housing Demand in the Short Run: An Analysis of Polytomous Choice," NBER Chapters, in: Explorations in Economic Research, Volume 3, number 1, pages 76-102 National Bureau of Economic Research, Inc.
    13. Cropper, Maureen L, et al, 1993. "Valuing Product Attributes Using Single Market Data: A Comparison of Hedonic and Discrete Choice Approaches," The Review of Economics and Statistics, MIT Press, vol. 75(2), pages 225-32, May.
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