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Explaining Household Location Choices Using A Spatial Probit Model

  • Ozturk, Erdogan
  • Irwin, Elena G.
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    A spatial probit model is estimated to test the influence of public services and neighborhood characteristics on relocation decisions of homebuyers in the Columbus, Ohio region. The model explicitly accounts for the spatial error autocorrelation that arises due to unobserved similarities across alternatives, which, if uncontrolled, results in inconsistent parameter estimates.

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    File URL: http://purl.umn.edu/20626
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    Paper provided by American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association) in its series 2001 Annual meeting, August 5-8, Chicago, IL with number 20626.

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    Date of creation: 2001
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    Handle: RePEc:ags:aaea01:20626
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    1. Rubinfeld, Daniel L & Shapiro, Perry & Roberts, Judith, 1987. "Tiebout Bias and the Demand for Local Public Schooling," The Review of Economics and Statistics, MIT Press, vol. 69(3), pages 426-37, August.
    2. Thomas J. Nechyba & Robert P. Strauss, 1997. "Community Choice and Local Public Services: A Discrete Choice Approach," NBER Working Papers 5966, National Bureau of Economic Research, Inc.
    3. Hoyt, William H. & Rosenthal, Stuart S., 1997. "Household Location and Tiebout: Do Families Sort According to Preferences for Locational Amenities?," Journal of Urban Economics, Elsevier, vol. 42(2), pages 159-178, September.
    4. Denis Bolduc & Bernard Fortin & Stephen Gordon, 1997. "Multinomial Probit Estimation of Spatially Interdependent Choices: An Empirical Comparison of Two New Techniques," International Regional Science Review, , vol. 20(1-2), pages 77-101, April.
    5. Hamilton, Bruce W, 1976. "The Effects of Property Taxes and Local Public Spending on Property Values: A Theoretical Comment," Journal of Political Economy, University of Chicago Press, vol. 84(3), pages 647-50, June.
    6. Pinkse, Joris & Slade, Margaret E., 1998. "Contracting in space: An application of spatial statistics to discrete-choice models," Journal of Econometrics, Elsevier, vol. 85(1), pages 125-154, July.
    7. Carlos Arias & THOMAS L. COX, 1999. "Maximum Simulated Likelihood: A Brief Introduction for Practitioners," Wisconsin-Madison Agricultural and Applied Economics Staff Papers 421, Wisconsin-Madison Agricultural and Applied Economics Department.
    8. David M. Brasington, 1999. "Which Measures of School Quality Does the Housing Market Value?," Journal of Real Estate Research, American Real Estate Society, vol. 18(3), pages 395-414.
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