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Measuring the effect of the real estate bubble: a house price index for Bilbao

In: Papers presented during the Narodowy Bank Polski Workshop: Recent trends in the real estate market and its analysis, 2013

Author

Listed:
  • Maria J. Barcena
  • Patricia Mendez
  • Maria B. Palacios
  • Fernando Tusell

Abstract

Houses are traded at relatively infrequent times and can hardly be standardized: two equally built and furnished houses may command widely different prices in the market on account of their different location or even orientation. Clearly, the computation of an index such as Laspeyres’ cannot be contemplated, both because of lack of standardization and infrequent trading. On the other hand, there is little market visibility; transaction prices are seldom published, further increasing the difficulties inherent to the construction of a house price index. In this paper we use advertised (selling) prices as a proxy of transaction prices, and geographically weighted hedonic models to account for heterogeneity in quality and location. This gives a workable alternative to conventional approaches with the added benefit that it can provide price information in near-real time.

Suggested Citation

  • Maria J. Barcena & Patricia Mendez & Maria B. Palacios & Fernando Tusell, 2013. "Measuring the effect of the real estate bubble: a house price index for Bilbao," Chapters from NBP Conference Publications, in: Hanna Augustyniak & Jacek Łaszek & Krzysztof Olszewski (ed.), Papers presented during the Narodowy Bank Polski Workshop: Recent trends in the real estate market and its analysis, 2013, chapter 15, pages 127-156, Narodowy Bank Polski.
    • Handle: RePEc:nbp:nbpchp:15
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    References listed on IDEAS

    as
    1. 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.
    2. Andrea Baranzini & José Ramirez & Caroline Schaerer & Philippe Thalmann (ed.), 2008. "Hedonic Methods in Housing Markets," Springer Books, Springer, number 978-0-387-76815-1, December.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
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    Cited by:

    1. 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.
    2. 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.

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    More about this item

    Keywords

    house prices; spatial econometrics; semi-parametric models;
    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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