IDEAS home Printed from https://ideas.repec.org/p/zbw/sfb373/200255.html
   My bibliography  Save this paper

Real estate valuation according to standardized methods: An empirical analysis

Author

Listed:
  • Schulz, Rainer

Abstract

Appraisals are needed for decision-making and for performance evaluation. Knowledge on the accuracy of valuation methods is of general interest for banks and investors. We assess the accuracy of the German Regulation on Valuation with monthly data on appraisals and prices for commercial apartment houses in Berlin, Germany from 1980 to 2000. The appraisals are compared with outcomes of the simpler capitalization method and are ranked better according to several prediction error measures. Nonparametric density estimates give the error distributions and investors can decide which method is preferable. Eventually, we explain short-run deviations between prices and appraisals by incompletely appraised object-specific factors and by market indicators.

Suggested Citation

  • 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.
    • Handle: RePEc:zbw:sfb373:200255
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/65337/1/726807524.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ling, David C & Naranjo, Andy, 1997. "Economic Risk Factors and Commercial Real Estate Returns," The Journal of Real Estate Finance and Economics, Springer, vol. 14(3), pages 283-307, May.
    2. Gourieroux,Christian & Monfort,Alain, 1997. "Time Series and Dynamic Models," Cambridge Books, Cambridge University Press, number 9780521423083, January.
    3. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    4. Englund, Peter & Ioannides, Yannis M., 1997. "House Price Dynamics: An International Empirical Perspective," Journal of Housing Economics, Elsevier, vol. 6(2), pages 119-136, June.
    5. Durbin, James & Koopman, Siem Jan, 2012. "Time Series Analysis by State Space Methods," OUP Catalogue, Oxford University Press, edition 2, number 9780199641178.
    6. R. H. Shumway & D. S. Stoffer, 1982. "An Approach To Time Series Smoothing And Forecasting Using The Em Algorithm," Journal of Time Series Analysis, Wiley Blackwell, vol. 3(4), pages 253-264, July.
    7. J. Hirshleifer, 1958. "On the Theory of Optimal Investment Decision," Journal of Political Economy, University of Chicago Press, vol. 66(4), pages 329-329.
    8. 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.
    9. Siem Jan Koopman & Neil Shephard & Jurgen A. Doornik, 1999. "Statistical algorithms for models in state space using SsfPack 2.2," Econometrics Journal, Royal Economic Society, vol. 2(1), pages 107-160.
    10. Kaplan, Steven N & Ruback, Richard S, 1995. "The Valuation of Cash Flow Forecasts: An Empirical Analysis," Journal of Finance, American Finance Association, vol. 50(4), pages 1059-1093, September.
    11. Spanos,Aris, 1999. "Probability Theory and Statistical Inference," Cambridge Books, Cambridge University Press, number 9780521424080.
    12. Mark G. Dotzour, 1988. "Quantifying Estimation Bias in Residential Appraisal," Journal of Real Estate Research, American Real Estate Society, vol. 3(3), pages 1-11.
    13. John M. Clapp & Carmelo Giaccotto, 2002. "Evaluating House Price Forecasts," Journal of Real Estate Research, American Real Estate Society, vol. 24(1), pages 1-26.
    14. Schulz, Rainer & Werwatz, Axel, 2002. "A simple state space model of house prices," SFB 373 Discussion Papers 2002,39, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    15. Chinloy, Peter & Cho, Man & Megbolugbe, Isaac F, 1997. "Appraisals, Transaction Incentives, and Smoothing," The Journal of Real Estate Finance and Economics, Springer, vol. 14(1-2), pages 89-111, Jan.-Marc.
    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. Bramh Dev Sharma, 2014. "Residential Estate Valuation Index (REVI): A Consumer Perspective," Management and Labour Studies, XLRI Jamshedpur, School of Business Management & Human Resources, vol. 39(3), pages 365-380, August.

    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.
    1. David de Antonio Liedo, 2014. "Nowcasting Belgium," Working Paper Research 256, National Bank of Belgium.
    2. Koopman, Siem Jan & Jungbacker, Borus & Hol, Eugenie, 2005. "Forecasting daily variability of the S&P 100 stock index using historical, realised and implied volatility measurements," Journal of Empirical Finance, Elsevier, vol. 12(3), pages 445-475, June.
    3. Hindrayanto, Irma & Koopman, Siem Jan & de Winter, Jasper, 2016. "Forecasting and nowcasting economic growth in the euro area using factor models," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1284-1305.
    4. Yasutomo Murasawa & Roberto S. Mariano, 2004. "Constructing a Coincident Index of Business Cycles Without Assuming a One-Factor Model," Econometric Society 2004 Far Eastern Meetings 710, Econometric Society.
    5. Hindrayanto, Irma & Koopman, Siem Jan & Ooms, Marius, 2010. "Exact maximum likelihood estimation for non-stationary periodic time series models," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2641-2654, November.
    6. Nikolaos Zirogiannis & Yorghos Tripodis, 2018. "Dynamic factor analysis for short panels: estimating performance trajectories for water utilities," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 27(1), pages 131-150, March.
    7. Dordonnat, Virginie & Koopman, Siem Jan & Ooms, Marius, 2012. "Dynamic factors in periodic time-varying regressions with an application to hourly electricity load modelling," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3134-3152.
    8. Dordonnat, V. & Koopman, S.J. & Ooms, M. & Dessertaine, A. & Collet, J., 2008. "An hourly periodic state space model for modelling French national electricity load," International Journal of Forecasting, Elsevier, vol. 24(4), pages 566-587.
    9. De Gooijer, Jan G. & Hyndman, Rob J., 2006. "25 years of time series forecasting," International Journal of Forecasting, Elsevier, vol. 22(3), pages 443-473.
    10. Zirogiannis, Nikolaos & Tripodis, Yorghos, 2014. "Dynamic Factor Analysis for Short Panels: Estimating Performance Trajectories for Water Utilities," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 170592, Agricultural and Applied Economics Association.
    11. Koopman, Siem Jan & van der Wel, Michel, 2013. "Forecasting the US term structure of interest rates using a macroeconomic smooth dynamic factor model," International Journal of Forecasting, Elsevier, vol. 29(4), pages 676-694.
    12. Raïsa Basselier & David Antonio Liedo & Geert Langenus, 2018. "Nowcasting Real Economic Activity in the Euro Area: Assessing the Impact of Qualitative Surveys," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 14(1), pages 1-46, April.
    13. Drew Creal & Siem Jan Koopman & Eric Zivot, 2008. "The Effect of the Great Moderation on the U.S. Business Cycle in a Time-varying Multivariate Trend-cycle Model," Tinbergen Institute Discussion Papers 08-069/4, Tinbergen Institute.
    14. Raggi, Davide & Bordignon, Silvano, 2012. "Long memory and nonlinearities in realized volatility: A Markov switching approach," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3730-3742.
    15. Scott Brave & R. Andrew Butters & Alejandro Justiniano, 2016. "Forecasting Economic Activity with Mixed Frequency Bayesian VARs," Working Paper Series WP-2016-5, Federal Reserve Bank of Chicago.
    16. Brave, Scott A. & Gascon, Charles & Kluender, William & Walstrum, Thomas, 2021. "Predicting benchmarked US state employment data in real time," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1261-1275.
    17. Tommaso Proietti, 2002. "Some Reflections on Trend-Cycle Decompositions with Correlated Components," Econometrics 0209002, University Library of Munich, Germany.
    18. Niels Haldrup & Carsten P. T. Rosenskjold, 2019. "A Parametric Factor Model of the Term Structure of Mortality," Econometrics, MDPI, vol. 7(1), pages 1-22, March.
    19. Mehmet Balcilar & Rangan Gupta & Stephen M. Miller, 2015. "The out-of-sample forecasting performance of nonlinear models of regional housing prices in the US," Applied Economics, Taylor & Francis Journals, vol. 47(22), pages 2259-2277, May.
    20. Motta, Anderson C. O. & Hotta, Luiz K., 2003. "Exact Maximum Likelihood and Bayesian Estimation of the Stochastic Volatility Model," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 23(2), November.

    More about this item

    Keywords

    Appraisal Accuracy; Discounted Value; House Prices; State Space Model;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • K00 - Law and Economics - - General - - - General (including Data Sources and Description)

    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:zbw:sfb373:200255. 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: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: https://edirc.repec.org/data/sfhubde.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.