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Neighborhood weight matrix in a spatial-quantile real estate modeling environment: Evidence from Brazil

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  • Bernardo Furtado

    ()

  • Frank van Oort

Abstract

This paper analysis two central influences on real estate urban market: (a) neighborhood as cognitively-perceived identity units, and (b) heterogeneity of preferences of households. In doing so, two methodological changes are applied. Firstly, a neighborhood spatial matrix is proposed and compared to regularly used matrices and, secondly, a spatial-quantile regression is tested. The results highlight the fact that spatial influence brought to regression models through weight matrix should be carefully used, and that the matrix’s choice might carry unobserved and unwanted effects into the estimation. Results also demonstrated that using information of neighborhood identity can optimize the understanding of city’s complex influence on real estate markets. Finally, the quantile estimation should always be tested against in real estate estimation, as preferences of households seem to differ significantly for different levels of prices.

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Bibliographic Info

Paper provided by European Regional Science Association in its series ERSA conference papers with number ersa10p424.

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Date of creation: Sep 2011
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Handle: RePEc:wiw:wiwrsa:ersa10p424

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  1. Zhenlin Yang & Liangjun Su, 2007. "Instrumental Variable Quantile Estimation of Spatial Autoregressive Models," Working Papers, Singapore Management University, School of Economics 05-2007, Singapore Management University, School of Economics.
  2. Smirnov, Oleg & Anselin, Luc, 2001. "Fast maximum likelihood estimation of very large spatial autoregressive models: a characteristic polynomial approach," Computational Statistics & Data Analysis, Elsevier, Elsevier, vol. 35(3), pages 301-319, January.
  3. Wheaton, William C., 2004. "Commuting, congestion, and employment dispersal in cities with mixed land use," Journal of Urban Economics, Elsevier, vol. 55(3), pages 417-438, May.
  4. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, Econometric Society, vol. 46(1), pages 33-50, January.
  5. Joachim Zietz & Emily Zietz & G. Sirmans, 2008. "Determinants of House Prices: A Quantile Regression Approach," The Journal of Real Estate Finance and Economics, Springer, Springer, vol. 37(4), pages 317-333, November.
  6. Roberta Capello & Peter Nijkamp, 2003. "The theoretical and methodological toolbox of urban economics: from and towards where?," ERSA conference papers, European Regional Science Association ersa03p510, European Regional Science Association.
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