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Evaluating Real Estate Valuation Systems

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Listed:
  • Shiller, Robert J
  • Weiss, Allan N

Abstract

A framework for comparing real estate valuation systems (including automated valuation models (AVMs) and current appraisal methods) is proposed. The density estimation and profit simulation (DEPS) method measures quality of a valuation system by simulating benefits to the mortgage lender who uses this method in mortgage underwriting to limit mortgage portfolio losses due to default. Related simple measures relevant to the selection of a valuation system are also discussed: skewness of the distribution of errors, correlation of valuation errors with current selling price errors, correlation of errors of the valuation system with errors of valuation systems used by competing mortgage lenders, and other measures. Copyright 1999 by Kluwer Academic Publishers

Suggested Citation

  • Shiller, Robert J & Weiss, Allan N, 1999. "Evaluating Real Estate Valuation Systems," The Journal of Real Estate Finance and Economics, Springer, vol. 18(2), pages 147-161, March.
    • Handle: RePEc:kap:jrefec:v:18:y:1999:i:2:p:147-61
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    Cited by:

    1. Miriam Steurer & Robert Hill, 2019. "Metrics for Evaluating the Performance of Automated Valuation Models," Graz Economics Papers 2019-02, University of Graz, Department of Economics.
    2. Steven Peterson & Albert B. Flanagan, 2009. "Neural Network Hedonic Pricing Models in Mass Real Estate Appraisal," Journal of Real Estate Research, American Real Estate Society, vol. 31(2), pages 147-164.
    3. Vicente Royuela & Miguel A. Vargas, 2009. "Defining Housing Market Areas Using Commuting and Migration Algorithms: Catalonia (Spain) as a Case Study," Urban Studies, Urban Studies Journal Limited, vol. 46(11), pages 2381-2398, October.
    4. Robert J. Shiller, 2014. "Speculative Asset Prices (Nobel Prize Lecture)," Cowles Foundation Discussion Papers 1936, Cowles Foundation for Research in Economics, Yale University.
    5. Schulz, Rainer, 2002. "Real estate valuation according to standardized methods: An empirical analysis," SFB 373 Discussion Papers 2002,55, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    6. Robert J. Shiller, 2014. "Speculative Asset Prices," American Economic Review, American Economic Association, vol. 104(6), pages 1486-1517, June.
    7. Rainer Schulz & Martin Wersing & Axel Werwatz, 2014. "Automated valuation modelling: a specification exercise," Journal of Property Research, Taylor & Francis Journals, vol. 31(2), pages 131-153, June.
    8. Tien Foo Sing & Jesse Jingye Yang & Shi Ming Yu, 2022. "Boosted Tree Ensembles for Artificial Intelligence Based Automated Valuation Models (AI-AVM)," The Journal of Real Estate Finance and Economics, Springer, vol. 65(4), pages 649-674, November.
    9. Rafal Zbyrowski, 2016. "The Application of the Shepard’s Interpolation for a Property Valuation (Zastosowanie metody Sheparda do szacowania nieruchomosci)," Research Reports, University of Warsaw, Faculty of Management, vol. 2(22), pages 249-256.

    More about this item

    JEL classification:

    • G20 - Financial Economics - - Financial Institutions and Services - - - General
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages

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