IDEAS home Printed from https://ideas.repec.org/p/gwc/wpaper/2010-004.html
   My bibliography  Save this paper

Evaluating Alternative Methods of Forecasting House Prices: A Post-Crisis Reassessment

Author

Listed:
  • William D. Larson

    (George Washington University)

Abstract

This paper compares the performance of different forecasting models of California house prices. Multivariate, theory-driven models are able to outperform a theoretical time series models across a battery of forecast comparison measures. Error correction models were best able to predict the turning point in the housing market, whereas univariate models were not. Similarly, even after the turning point occurred, error correction models were still able to outperform univariate models based on MSFE, bias, and forecast encompassing statistics and tests. These results highlight the importance of incorporating theoretical economic relationships into empirical forecasting models.

Suggested Citation

  • William D. Larson, 2010. "Evaluating Alternative Methods of Forecasting House Prices: A Post-Crisis Reassessment," Working Papers 2010-004, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting, revised Feb 2011.
    • Handle: RePEc:gwc:wpaper:2010-004
    as

    Download full text from publisher

    File URL: https://www2.gwu.edu/~forcpgm/2010-004.pdf
    File Function: Second version, 2011
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Anthony Pennington-Cross, 2005. "Aggregation bias and the repeat sales price index," BIS Papers chapters, in: Bank for International Settlements (ed.), Real estate indicators and financial stability, volume 21, pages 323-335, Bank for International Settlements.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zietz, Joachim & Traian, Anca, 2014. "When was the U.S. housing downturn predictable? A comparison of univariate forecasting methods," The Quarterly Review of Economics and Finance, Elsevier, vol. 54(2), pages 271-281.
    2. Berndt, Antje & Hollifield, Burton & Sandås, Patrik, 2014. "How Subprime Borrowers and Mortgage Brokers Shared the Pie," Working Paper Series 286, Sveriges Riksbank (Central Bank of Sweden).
    3. repec:zbw:rwirep:0294 is not listed on IDEAS
    4. Philipp an de Meulen & Martin Micheli & Torsten Schmidt, 2011. "Forecasting House Prices in Germany," Ruhr Economic Papers 0294, Rheinisch-Westfälisches Institut für Wirtschaftsforschung, Ruhr-Universität Bochum, Universität Dortmund, Universität Duisburg-Essen.
    5. an de Meulen, Philipp & Micheli, Martin & Schmidt, Torsten, 2011. "Forecasting House Prices in Germany," Ruhr Economic Papers 294, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.

      More about this item

      Keywords

      house prices; forecasting; forecast comparison; forecast encompassing;
      All these keywords.

      JEL classification:

      • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
      • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
      • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

      Statistics

      Access and download statistics

      Corrections

      All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gwc:wpaper:2010-004. See general information about how to correct material in RePEc.

      If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

      If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

      If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

      For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: GW Economics Department (email available below). General contact details of provider: https://edirc.repec.org/data/pfgwuus.html .

      Please note that corrections may take a couple of weeks to filter through the various RePEc services.

      IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.