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A house price-at-risk model to monitor the downside risk for the spanish housing market

Author

Listed:
  • Gergely Ganics

    (Banco de España)

  • María Rodríguez-Moreno

    (Banco de España)

Abstract

We present a house price-at-risk (HaR) model that fits the historical developments in the Spanish housing market. By means of quantile regressions we show that a model including quarterly real house price growth, a misalignment measure and a consumer confidence index is able to accurately forecast the developments in the Spanish housing market up to two years ahead. We also show how the HaR model can be used to monitor the downside risk.

Suggested Citation

  • Gergely Ganics & María Rodríguez-Moreno, 2022. "A house price-at-risk model to monitor the downside risk for the spanish housing market," Working Papers 2244, Banco de España.
    • Handle: RePEc:bde:wpaper:2244
    DOI: https://doi.org/10.53479/29472
    as

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    References listed on IDEAS

    as
    1. M. C. Jones & M. J. Faddy, 2003. "A skew extension of the t‐distribution, with applications," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 65(1), pages 159-174, February.
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    More about this item

    Keywords

    house price-at-risk; house prices; quantile regressions;
    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
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • G01 - Financial Economics - - General - - - Financial Crises
    • 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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