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Measuring the Effect of the Real Estate Bubble: a House Price Index for Bilbao

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  • Bárcena Ruiz, María Jesús
  • Menéndez, Patricia
  • Palacios, María Blanca
  • Tusell Palmer, Fernando Jorge

Abstract

A spatio-temporal model is proposed aimed at producing an index of housing prices. A hedonic model with geographically varying coefficients is coupled with a non parametric estimation of the trend, whence a price index is derived.

Suggested Citation

  • Bárcena Ruiz, María Jesús & Menéndez, Patricia & Palacios, María Blanca & Tusell Palmer, Fernando Jorge, 2011. "Measuring the Effect of the Real Estate Bubble: a House Price Index for Bilbao," BILTOKI 1134-8984, Universidad del País Vasco - Departamento de Economía Aplicada III (Econometría y Estadística).
    • Handle: RePEc:ehu:biltok:5463
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    File URL: https://addi.ehu.es/handle/10810/5463
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    References listed on IDEAS

    as
    1. Bourassa, Steven C. & Hoesli, Martin & Sun, Jian, 2006. "A simple alternative house price index method," Journal of Housing Economics, Elsevier, vol. 15(1), pages 80-97, March.
    2. Ghislain Geniaux & Claude Napoléone, 2008. "Semi-Parametric Tools for Spatial Hedonic Models: An Introduction to Mixed Geographically Weighted Regression and Geoadditive Models," Springer Books, in: Andrea Baranzini & José Ramirez & Caroline Schaerer & Philippe Thalmann (ed.), Hedonic Methods in Housing Markets, chapter 5, pages 101-127, Springer.
    3. Daniel P. McMillen & Christopher Redfearn, 2007. "Estimation, Interpretation, and Hypothesis Testing for Nonparametric Hedonic House Price Functions," Working Paper 8550, USC Lusk Center for Real Estate.
    4. Håvard Rue & Sara Martino & Nicolas Chopin, 2009. "Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 71(2), pages 319-392, April.
    5. Simon N. Wood, 2004. "Stable and Efficient Multiple Smoothing Parameter Estimation for Generalized Additive Models," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 673-686, January.
    6. David Wheeler & Michael Tiefelsdorf, 2005. "Multicollinearity and correlation among local regression coefficients in geographically weighted regression," Journal of Geographical Systems, Springer, vol. 7(2), pages 161-187, June.
    7. Andrea Baranzini & José Ramirez & Caroline Schaerer & Philippe Thalmann (ed.), 2008. "Hedonic Methods in Housing Markets," Springer Books, Springer, number 978-0-387-76815-1, July.
    8. John M. Clapp, 2004. "A Semiparametric Method for Estimating Local House Price Indices," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 32(1), pages 127-160, March.
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    Cited by:

    1. M. Bárcena & P. Menéndez & M. Palacios & F. Tusell, 2014. "Alleviating the effect of collinearity in geographically weighted regression," Journal of Geographical Systems, Springer, vol. 16(4), pages 441-466, October.
    2. Widłak, Marta & Waszczuk, Joanna & Olszewski, Krzysztof, 2014. "Spatial and hedonic analysis of house price dynamics in Warsaw," MPRA Paper 60479, University Library of Munich, Germany.

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    More about this item

    Keywords

    house prices; price index; GWR; geographically weighted regression;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • R21 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Housing Demand

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