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Examining the vintage effect in hedonic pricing using spatially varying coefficients models: a case study of single-family houses in the Canton of Zurich

Author

Listed:
  • Jakob A. Dambon

    (University of Zurich
    Lucerne University of Applied Sciences and Arts)

  • Stefan S. Fahrländer

    (Fahrländer Partner Raumentwicklung)

  • Saira Karlen

    (Fahrländer Partner Raumentwicklung)

  • Manuel Lehner

    (Fahrländer Partner Raumentwicklung)

  • Jaron Schlesinger

    (Fahrländer Partner Raumentwicklung)

  • Fabio Sigrist

    (Lucerne University of Applied Sciences and Arts)

  • Anna Zimmermann

    (Fahrländer Partner Raumentwicklung)

Abstract

This article examines the spatially varying effect of age on single-family house (SFH) prices. Age has been shown to be a key driver for house depreciation and is usually associated with a negative price effect. In practice, however, there exist deviations from this behavior which are referred to as vintage effects. We estimate a spatially varying coefficients (SVC) model to investigate the spatial structures of vintage effects on SFH pricing. For SFHs in the Canton of Zurich, Switzerland, we find substantial spatial variation in the age effect. In particular, we find a local, strong vintage effect primarily in urban areas compared to pure depreciative age effects in rural locations. Using cross validation, we assess the potential improvement in predictive performance by incorporating spatially varying vintage effects in hedonic models. We find a substantial improvement in out-of-sample predictive performance of SVC models over classical spatial hedonic models.

Suggested Citation

  • Jakob A. Dambon & Stefan S. Fahrländer & Saira Karlen & Manuel Lehner & Jaron Schlesinger & Fabio Sigrist & Anna Zimmermann, 2022. "Examining the vintage effect in hedonic pricing using spatially varying coefficients models: a case study of single-family houses in the Canton of Zurich," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 158(1), pages 1-14, December.
    • Handle: RePEc:spr:sjecst:v:158:y:2022:i:1:d:10.1186_s41937-021-00080-2
    DOI: 10.1186/s41937-021-00080-2
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    References listed on IDEAS

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    Cited by:

    1. Fabienne Helfer & Volker Grossmann & Aderonke Osikominu, 2023. "How does immigration affect housing costs in Switzerland?," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 159(1), pages 1-31, December.

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    More about this item

    Keywords

    Gaussian process; Spatial statistics; Real estate; Mass appraisal;
    All these keywords.

    JEL classification:

    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • R31 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Housing Supply and Markets
    • R32 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Other Spatial Production and Pricing Analysis

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