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Estimating Housing Prices: A Proposal with Spatially Correlated Data

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  • Jose Montero
  • Beatriz Larraz

Abstract

The price of housing per square meter and the trend observed over the last few years is one of the issues that most concerns Spanish citizens and subsequently their political and economic representatives. However, in spite of the importance of space in the real estate market, official averages do not take into account the spatial correlation of housing prices. In order to solve this handicap, we propose the kriging the mean method to estimate mean housing prices. This method provides the best unbiased linear estimation taking into account spatially correlated data. Copyright International Atlantic Economic Society 2010

Suggested Citation

  • Jose Montero & Beatriz Larraz, 2010. "Estimating Housing Prices: A Proposal with Spatially Correlated Data," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 16(1), pages 39-51, February.
    • Handle: RePEc:kap:iaecre:v:16:y:2010:i:1:p:39-51:10.1007/s11294-009-9244-5
    DOI: 10.1007/s11294-009-9244-5
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    References listed on IDEAS

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    1. John M. Clapp & Hyon–Jung Kim & Alan E. Gelfand, 2002. "Predicting Spatial Patterns of House Prices Using LPR and Bayesian Smoothing," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 30(4), pages 505-532.
    2. Allan Din & Martin Hoesli & Andre Bender, 2001. "Environmental Variables and Real Estate Prices," Urban Studies, Urban Studies Journal Limited, vol. 38(11), pages 1989-2000, October.
    3. Dubin, Robin A, 1998. "Predicting House Prices Using Multiple Listings Data," The Journal of Real Estate Finance and Economics, Springer, vol. 17(1), pages 35-59, July.
    4. repec:kap:iaecre:v:14:y:2008:i:4:p:407-421 is not listed on IDEAS
    5. Yiu, C.Y. & Tam, C.S., 2007. "Housing price gradient with two workplaces -- An empirical study in Hong Kong," Regional Science and Urban Economics, Elsevier, vol. 37(3), pages 413-429, May.
    6. Bradford Case & John Clapp & Robin Dubin & Mauricio Rodriguez, 2004. "Modeling Spatial and Temporal House Price Patterns: A Comparison of Four Models," The Journal of Real Estate Finance and Economics, Springer, vol. 29(2), pages 167-191, September.
    7. Alan E. Gelfand & Mark D. Ecker & John R. Knight & C. F. Sirmans, 2004. "The Dynamics of Location in Home Price," The Journal of Real Estate Finance and Economics, Springer, vol. 29(2), pages 149-166, September.
    8. Sun Sheng Han, 2004. "Spatial Structure of Residential Property-Value Distribution in Beijing and Jakarta," Environment and Planning A, , vol. 36(7), pages 1259-1283, July.
    9. Beatriz Larraz-Iribas & Jose-Luis Alfaro-Navarro, 2008. "Asymmetric Behaviour of Spanish Regional House Prices," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 14(4), pages 407-421, November.
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    Citations

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    Cited by:

    1. Beatriz Larraz, 2011. "An Expert System for Online Residential Properties Valuation," Review of Economics & Finance, Better Advances Press, Canada, vol. 1, pages 69-82, April.
    2. Kilgarriff, Paul & Charlton, Martin & Foley, Ronan & O'Donoghue, Cathal, 2019. "The impact of housing consumption value on the spatial distribution of welfare," Journal of Housing Economics, Elsevier, vol. 43(C), pages 118-130.
    3. Karolien De Bruyne & Jan Van Hove, 2013. "Explaining the spatial variation in housing prices: an economic geography approach," Applied Economics, Taylor & Francis Journals, vol. 45(13), pages 1673-1689, May.
    4. José-María Montero & Coro Chasco & Beatriz Larraz, 2010. "Building an environmental quality index for a big city: a spatial interpolation approach combined with a distance indicator," Journal of Geographical Systems, Springer, vol. 12(4), pages 435-459, December.
    5. José-María Montero & Román Mínguez & Gema Fernández-Avilés, 2018. "Housing price prediction: parametric versus semi-parametric spatial hedonic models," Journal of Geographical Systems, Springer, vol. 20(1), pages 27-55, January.

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    More about this item

    Keywords

    Kriging the mean estimator; Covariogram; Spatial correlation; Housing prices; C13; C21; R31;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • R31 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Housing Supply and Markets

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