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

Author information:

Áron Horváth: ELTINGA Centre for Real Estate Research, Head; Centre for Economic and Regional Studies – Hungarian Academy of Sciences, Research Fellow. E-mail: horvathar@eltinga.hu

Blanka Imre: Università Bocconi, PhD student. E-mail: blanka.imre@unibocconi.it

Zoltán Sápi: ELTINGA Centre for Real Estate Research, Analyst. E-mail: sapiz@eltinga.hu

Cite as (APA):

Horváth, Á., Imre, B., & Sápi, Z. (2016). The International Practice of Statistical Property Valuation Methods and the Possibilities of Introducing Automated Valuation Models in Hungary. Financial and Economic Review, 15(4), 45–64. https://hitelintezetiszemle.mnb.hu/en/aron-horvath-blanka-imre-zoltan-sapi

Column:

Study

Journal of Economic Literature (JEL) codes:

C15, C45, G21

Keywords:

mortgage, collateral valuation, automated valuation model, statistical valuation

References:

Anselin, L. (1988): Spatial Econometrics: Methods and Models. Kluwer Academic Publishers, Dordrecht, 284 p.

Anselin, L. (1990): Spatial dependence and spatial structural instability in applied regression analysis. Journal of Regional Science, Vol. 30, May, pp. 185–207.

Anselin, L. (2009): Spatial Regression. In: A.S. Fotheringham – P.A. Rogerson (Eds.). The SAGE Handbook of Spatial Analysis. SAGE Publications Ltd., London, pp. 255–276.

Anselin, L. (2010): Thirty years of spatial econometrics. Papers in Regional Science, Vol. 89, March, pp. 3–25.

Békés, G. – Horváth, Á. – Sápi, Z. (2016): Housing prices and municipality-based differences (Lakóingatlan-árak és települési különbségek). MT-DP – 2016/21, Institute of Economics, Centre for Economic and Regional Studies of the Hungarian Academy of Sciences, Budapest, p. 39

Bourassa, S.C. – Hoesli, M. – Peng, V.S. (2003): Do housing submarkets really matter? Journal of Housing Economics, Vol. 12, March, pp. 12–28.

Cassetti, E. (1997): The expansion method, mathematical modeling, and spatial econometrics. International Regional Science Review, Vol. 20, April, pp. 9–33.

Clapp, J.M. – O’Connor, P.M. (2008): Best practice automated valuation models of time and space. https://www.researchgate.net/publication/253052334_Best_Practice_Automated_Valuation_Models_of_Time_and_Space. Downloaded: 2 October 2016

Coulson, E. (2008): Hedonic methods and housing markets. Unpublished manuscript, Penn State University, Pennsylvania.

d’Amato, M. – Siniak, N. (2008): Using Fuzzy Numbers in Mass Appraisal: The Case of the Belarusian Property Market. In: T. Kauko – M. d’Amato (Eds.): Mass Appraisal Methods: An International Perspective for Property Valuers, Wiley-Blackwell, Oxford, pp. 91–107.

Davidson, R. – MacKinnon, J.G. (1981): Several tests for model specification in the presence of alternative hypotheses. Econometrica, Vol.49., May, pp. 781–793.

Elhorst, J.P. (2010): Applied spatial econometrics: Raising the bar. Spatial Economic Analysis, Vol. 5, March, pp. 9–28.

EMF – EAA (2016): Joint Paper on the use of automated valuation models in Europe. http://hb.betterregulation.com/external/EMF_EAA Joint Paper on Automated Valuation Models (AVMs) in Europe 09 May 16.pdf. Downloaded: 2 October 2016

Fotheringham, A.S. – Rogerson, P.A. (2009): The SAGE Handbook of Spatial Analysis. SAGE Publications Ltd., London, 511 p.

Fotheringham, A.S. – Brunsdon, C. – Charlton, M. (2002): Geographically Weighted Regression: the analysis of spatially varying relationships. John Wiley & Sons Ltd., Chichester, 269 p.

Gelfand, A. – Kim, H.-J. – Sirmans, C.F – Banerjee, S. (2003): Spatial modeling with spatially varying coefficient processes. Journal of the American Statistical Association, Vol. 98, June, pp. 387–396.

Gibbons, S. – Machin, S. (2003): Valuing English primary schools. Journal of Urban Economics, Vol. 53, March, pp. 197–219.

González, M.A.S. (2008): Developing Mass Appraisal Models with Fuzzy Systems. In: T. Kauko – M. d’Amato (Eds.): Mass Appraisal Methods: An International Perspective for Property Valuers, Wiley-Blackwell, Oxford, pp. 183–202.

Goodman, A. – Thibodeau, T. (2003): Housing market segmentation and hedonic prediction accuracy. Journal of Housing Economics, Vol. 12., September, pp. 181–201.

Gress, B. (2004): Semi-Parametric Spatial Autocovariance Models. PhD thesis. CA: University of California, Riverside.

Henderson, D.J. – Ullah, A. (2005): A nonparametric random effects estimator. Economic Letters, Vol.88., September, pp. 403–407.

Kain, J.F. – Quigley, J.M. (1970): Measuring the value of housing quality. Journal of the American Statistical Association, Vol. 65, June, pp. 532–548.

Kauko, T. – d’Amato, M. (2008a): Mass Appraisal Methods: An International Perspective for Property Valuers, Wiley-Blackwell, Oxford, 324 p.

Kauko, T. – d’Amato, M. (2008b): Introduction: Suitability Issues in Mass Appraisal Methodology. In: T. Kauko – M. d’Amato (Eds.): Mass Appraisal Methods: An International Perspective for Property Valuers, Wiley-Blackwell, Oxford, pp. 1–24.

Lee, Y.-L. – Jung, C. – Kuang, Y.Y. (2003): Fair Evaluation of real Estate Value in Urban Area via Fuzzy Theory. 10th ERES Conference, Helsinki, Finland, 10-13. June

LeSage, J. – Pace, R.K. (2009): Introduction to Spatial Econometrics. Taylor & Francis, Boca Raton, 374 p.

Lughofer, E. – Trawiński, B. – Trawiński, K. – Kempa, O. – Lasota, T. (2011): On employing fuzzy modeling algorithms for the valuation of residential premises. Information Sciences, Vol.181., December, pp. 5123–5142.

MacQueen, J. (1967): Some methods for classification and analysis of multivariate observations. In: L.M. Le Cam – J. Neyman (Eds.): Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability. Volume I: Theory of Statistics, University of California Press, Berkeley and Los Angeles, pp. 281–297.

Manski, C.F. (1993): Identification of endogenous social effects: the reflection problem. Review of Economic Studies, Vol. 60, July, pp. 531–542.

Mimis, A. – Rovolis, A. – Stamou, M. (2013): Property valuation with artificial neural network: The case of Athens. Journal of Property Research, Vol. 30, June, pp. 128–143.

Nourse, H. (1963): The effect of public housing on property values in St Louis. Land Economics, Vol. 39, November, pp. 433-441.

Pagourtzi, E. – Assimakopoulos, V. – Hatzichristos, T. – French, N. (2003): Real estate appraisal: A review of valuation methods. Journal of Property Investment & Finance, 21 (4), pp. 383–401.

Peterson, S. – Flanagan, A. (2009): Neural network hedonic pricing models in mass real estate appraisal. Journal of Real Estate Research, 31(2), pp. 147–164.

Pinkse, J. – Slade, M.E. – Brett, C. (2002): Spatial price competition: A semiparametric approach. Econometrica, Vol. 70, May, pp. 1111–1153.

Ridker, R.G. – Henning, J.A. (1967): The determinants of residential property values with special reference to air pollution. Review of Economics and Statistics, Vol. 49, May, pp.246– 257.

Rosen, S. (1974): Hedonic prices and implicit markets: Product differentiation in pure competition. Journal of Political Economics, Vol.82., January-February, pp. 34–55.

Rossini, P. – Kershaw, P. (2005): Using a hybrid automated valuation model to estimate capital and site values. Eleventh Annual Pacific-Rim Real Estate Society Conference, Melbourne Australia, January 23rd – 27th January, 2005.

Sui, D.Z. (1992): A Fuzzy GIS Modeling Approach for Urban Land Evaluation. Computer Environment and Urban Systems, 16(2), pp. 101–115.