IDEAS home Printed from https://ideas.repec.org/a/mnb/finrev/v15y2016i4p45-64.html
   My bibliography  Save this article

The International Practice of Statistical Property Valuation Methods and the Possibilities of Introducing Automated Valuation Models in Hungary

Author

Listed:
  • Áron Horváth

    (Head of the ELTINGA Centre for Real Estate Research and research fellow at the Institute of Economics, Centre for Economic and Regional Studies of the Hungarian Academy of Sciences)

  • Blanka Imre

    (PhD student in economics at Universita Bocconi)

  • Zoltán Sápi

    (Analyst at the ELTINGA Centre for Real Estate Research)

Abstract

In the wake of regulatory, information technology and methodological changes, statistical property valuation has gained traction in Hungary. This paper looks at the available methods of appraisal based on the literature. We provide an overview of the advantages and drawbacks of the currently known methods. Based on these, automated valuation models (AVMs) can be readily introduced alongside the estimated median value based methods used so far. For real estate industryspecific reasons, the introduction of parametric hedonic estimates supplemented with spatial correlations can be expected for the time being. The better performance of statistical models would need improved quality of duties office data.

Suggested Citation

  • Áron Horváth & Blanka Imre & Zoltán Sápi, 2016. "The International Practice of Statistical Property Valuation Methods and the Possibilities of Introducing Automated Valuation Models in Hungary," Financial and Economic Review, Magyar Nemzeti Bank (Central Bank of Hungary), vol. 15(4), pages 45-64.
    • Handle: RePEc:mnb:finrev:v:15:y:2016:i:4:p:45-64
    as

    Download full text from publisher

    File URL: http://english.hitelintezetiszemle.hu/letoltes/aron-horvath-blanka-imre-zoltan-sapi.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Angelos Mimis & Antonis Rovolis & Marianthi Stamou, 2013. "Property valuation with artificial neural network: the case of Athens," Journal of Property Research, Taylor & Francis Journals, vol. 30(2), pages 128-143, June.
    2. Davidson, Russell & MacKinnon, James G, 1981. "Several Tests for Model Specification in the Presence of Alternative Hypotheses," Econometrica, Econometric Society, vol. 49(3), pages 781-793, May.
    3. Hugh O. Nourse, 1963. "The Effect of Public Housing on Property Values in St. Louis," Land Economics, University of Wisconsin Press, vol. 39(4), pages 433-441.
    4. Henderson, Daniel J. & Ullah, Aman, 2005. "A nonparametric random effects estimator," Economics Letters, Elsevier, vol. 88(3), pages 403-407, September.
    5. Goodman, Allen C. & Thibodeau, Thomas G., 2003. "Housing market segmentation and hedonic prediction accuracy," Journal of Housing Economics, Elsevier, vol. 12(3), pages 181-201, September.
    6. Young-Lung Lee & Chang Jung & Yih Yeh Kuang, 2003. "Fair Evaluation of real Estate Value in Urban Area via Fuzzy Theory," ERES eres2003_198, European Real Estate Society (ERES).
    7. 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.
    8. Gibbons, Steve & Machin, Stephen, 2003. "Valuing English primary schools," Journal of Urban Economics, Elsevier, vol. 53(2), pages 197-219, March.
    9. Charles F. Manski, 1993. "Identification of Endogenous Social Effects: The Reflection Problem," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 60(3), pages 531-542.
    10. Joris Pinkse & Margaret E. Slade & Craig Brett, 2002. "Spatial Price Competition: A Semiparametric Approach," Econometrica, Econometric Society, vol. 70(3), pages 1111-1153, May.
    11. Rosen, Sherwin, 1974. "Hedonic Prices and Implicit Markets: Product Differentiation in Pure Competition," Journal of Political Economy, University of Chicago Press, vol. 82(1), pages 34-55, Jan.-Feb..
    12. Luc Anselin, 2010. "Thirty years of spatial econometrics," Papers in Regional Science, Wiley Blackwell, vol. 89(1), pages 3-25, March.
    13. J. Elhorst, 2010. "Applied Spatial Econometrics: Raising the Bar," Spatial Economic Analysis, Taylor & Francis Journals, vol. 5(1), pages 9-28.
    14. Gelfand A.E. & Kim H-J. & Sirmans C.F. & Banerjee S., 2003. "Spatial Modeling With Spatially Varying Coefficient Processes," Journal of the American Statistical Association, American Statistical Association, vol. 98, pages 387-396, January.
    Full references (including those not matched with items on IDEAS)

    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. Nguyen-Hoang, Phuong & Yinger, John, 2011. "The capitalization of school quality into house values: A review," Journal of Housing Economics, Elsevier, vol. 20(1), pages 30-48, March.
    2. Jorge Luis Casanova Ferrando, 2019. "The Airbnb Effect on theRental Market: the Case of Madrid," Studies on the Spanish Economy eee2019-34, FEDEA.
    3. Faroek Lazrak & Peter Nijkamp & Piet Rietveld & Jan Rouwendal, 2014. "The market value of cultural heritage in urban areas: an application of spatial hedonic pricing," Journal of Geographical Systems, Springer, vol. 16(1), pages 89-114, January.
    4. Thomas M. Fullerton & Arturo Bujanda, 2018. "Commercial property values in a border metropolitan economy," Asia-Pacific Journal of Regional Science, Springer, vol. 2(2), pages 337-360, August.
    5. Baltagi, Badi H. & Fingleton, Bernard & Pirotte, Alain, 2014. "Spatial lag models with nested random effects: An instrumental variable procedure with an application to English house prices," Journal of Urban Economics, Elsevier, vol. 80(C), pages 76-86.
    6. Füss, Roland & Koller, Jan A., 2016. "The role of spatial and temporal structure for residential rent predictions," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1352-1368.
    7. Tsusaka, Takuji W. & Kajisa, Kei & Pede, Valerien O. & Aoyagi, Keitaro, 2015. "Neighborhood effects and social behavior: The case of irrigated and rainfed farmers in Bohol, the Philippines," Journal of Economic Behavior & Organization, Elsevier, vol. 118(C), pages 227-246.
    8. Katarina Zigova, 2017. "Specifying Social Weight Matrices of Researcher Networks: The Case of Academic Economists," Working Paper Series of the Department of Economics, University of Konstanz 2017-10, Department of Economics, University of Konstanz.
    9. Frank M. Fossen & Lukas Mergele & Nicolas Pardo, 2017. "Fueling fiscal interactions: commodity price shocks and local government spending in Colombia," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 24(4), pages 616-651, August.
    10. Roberto Ezcurra & Vicente Rios, 2015. "Volatility and Regional Growth in Europe: Does Space Matter?," Spatial Economic Analysis, Taylor & Francis Journals, vol. 10(3), pages 344-368, September.
    11. Kun Duan & Tapas Mishra & Mamata Parhi & Simon Wolfe, 2019. "How Effective are Policy Interventions in a Spatially-Embedded International Real Estate Market?," The Journal of Real Estate Finance and Economics, Springer, vol. 58(4), pages 596-637, May.
    12. Sylvia Y He, 2017. "A hierarchical estimation of school quality capitalisation in house prices in Orange County, California," Urban Studies, Urban Studies Journal Limited, vol. 54(14), pages 3337-3359, November.
    13. Simon K.C. Cheung, 2017. "A Localized Model for Residential Property Valuation: Nearest Neighbor with Attribute Differences," International Real Estate Review, Global Social Science Institute, vol. 20(2), pages 221-250.
    14. Shengxiao Li & Luoye Chen & Pengjun Zhao, 2019. "The impact of metro services on housing prices: a case study from Beijing," Transportation, Springer, vol. 46(4), pages 1291-1317, August.
    15. Yan Liu & Linchuan Yang & Kwong Wing Chau, 2020. "Impacts of Tourism Demand on Retail Property Prices in a Shopping Destination," Sustainability, MDPI, vol. 12(4), pages 1-14, February.
    16. William Cheung & Lewen Guo & Yuichiro Kawaguchi, 2021. "Automated valuation model for residential rental markets: evidence from Japan," Journal of Spatial Econometrics, Springer, vol. 2(1), pages 1-34, December.
    17. Stephen A. Samaha & Wagner A. Kamakura, 2008. "Assessing the Market Value of Real Estate Property with a Geographically Weighted Stochastic Frontier Model," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 36(4), pages 717-751, December.
    18. Beatriz Larraz, 2011. "An Expert System for Online Residential Properties Valuation," Review of Economics & Finance, Better Advances Press, Canada, vol. 1, pages 69-82, April.
    19. Germán M. Izón & Michael S. Hand & Daniel W. Mccollum & Jennifer A. Thacher & Robert P. Berrens, 2016. "Proximity to Natural Amenities: A Seemingly Unrelated Hedonic Regression Model with Spatial Durbin and Spatial Error Processes," Growth and Change, Wiley Blackwell, vol. 47(4), pages 461-480, December.
    20. Zhou, Yiwei & Wang, Xiaokun & Holguín-Veras, José, 2016. "Discrete choice with spatial correlation: A spatial autoregressive binary probit model with endogenous weight matrix (SARBP-EWM)," Transportation Research Part B: Methodological, Elsevier, vol. 94(C), pages 440-455.

    More about this item

    Keywords

    mortgage; collateral valuation; automated valuation model; statistical valuation;
    All these keywords.

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages

    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:mnb:finrev:v:15:y:2016:i:4:p:45-64. 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: Morvay Endre (email available below). General contact details of provider: https://edirc.repec.org/data/mnbgvhu.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.