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Hedonic-based price indexes for housing: theory, estimation, and index construction

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  • Nancy Wallace

Abstract

Housing price indexes should not confound the effect of changes in quality with the effects of changing house prices. A recent nonparametric regression technique, loess, allows flexible estimation of the hedonic price function and centers the estimation at fixed points, such as the beginning or ending period housing characteristics. Indexes using these estimates are consistent with the requirements of Laspeyres and Paasche price indexes. The technique is used to obtain indexes for fifteen municipalities in Alameda County from 1970:Q1 through 1995:Q1. The nonparametric hedonic-based indexes provide better controls for the effect of quality evolution on price movements than alternative methods.

Suggested Citation

  • Nancy Wallace, 1996. "Hedonic-based price indexes for housing: theory, estimation, and index construction," Economic Review, Federal Reserve Bank of San Francisco, pages 34-48.
    • Handle: RePEc:fip:fedfer:y:1996:p:34-48:n:3
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    1. Case, Karl E & Shiller, Robert J, 1989. "The Efficiency of the Market for Single-Family Homes," American Economic Review, American Economic Association, vol. 79(1), pages 125-137, March.
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    Cited by:

    1. Diego Vílchez, 2015. "Assessing the House Price Dynamics in Lima," IHEID Working Papers 09-2015, Economics Section, The Graduate Institute of International Studies.
    2. Javier Escobal, 2000. "Costo de transacción en la agricultura peruana: una primera aproximación a su medición e impacto," Otras investigaciones, Consorcio de Investigación Económica y Social.
    3. A. Decoster & K. De Swerdt, 2006. "Why and How to Construct a Genuine Belgian Price Index of House Sales," Review of Business and Economic Literature, KU Leuven, Faculty of Economics and Business (FEB), Review of Business and Economic Literature, vol. 0(2), pages 309-330.
    4. Victor Ginsburgh & Jianping Mei & Michael Moses, 2006. "On the computation of art indices in art," ULB Institutional Repository 2013/7290, ULB -- Universite Libre de Bruxelles.
    5. Ghysels, Eric & Plazzi, Alberto & Valkanov, Rossen & Torous, Walter, 2013. "Forecasting Real Estate Prices," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 509-580, Elsevier.
    6. John Krainer, 1999. "Real estate liquidity," Economic Review, Federal Reserve Bank of San Francisco, pages 14-26.
    7. Richard Meese & Nancy Wallace, 2003. "House Price Dynamics and Market Fundamentals: The Parisian Housing Market," Urban Studies, Urban Studies Journal Limited, vol. 40(5-6), pages 1027-1045, May.
    8. Olivier Schöni, 2014. "Asymptotic Properties of Imputed Hedonic Price Indices," SERC Discussion Papers 0166, Centre for Economic Performance, LSE.
    9. Charles Ka Yui Leung & Kelvin Siu Kei Wong & Patrick Wai Yin Cheung, 2007. "On the Stability of the Implicit Prices of Housing Attributes: A Dynamic Theory and Some Evidence," International Real Estate Review, Global Social Science Institute, vol. 10(2), pages 66-93.
    10. W. Brunauer & S. Lang & P. Wechselberger & S. Bienert, 2010. "Additive Hedonic Regression Models with Spatial Scaling Factors: An Application for Rents in Vienna," The Journal of Real Estate Finance and Economics, Springer, vol. 41(4), pages 390-411, November.
    11. Vílchez, Diego, 2015. "Evaluando las Dinámicas de Precios en el Sector Inmobiliario: Evidencia para Perú," Working Papers 2015-013, Banco Central de Reserva del Perú.

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    Prices; Housing; California;
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