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Mass Appraisal Models of Real Estate in the 21st Century: A Systematic Literature Review

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  • Daikun Wang

    (Department of Geography and Resource Management, The Chinese University of Hong Kong, Shatin, New Territories 999077, Hong Kong)

  • Victor Jing Li

    (Department of Geography and Resource Management, The Chinese University of Hong Kong, Shatin, New Territories 999077, Hong Kong
    Institute of Future Cities, The Chinese University of Hong Kong, Shatin, New Territories 999077, Hong Kong)

Abstract

With the increasing volume and active transaction of real estate properties, mass appraisal has been widely adopted in many countries for different purposes, including assessment of property tax. In this paper, 104 papers are selected for the systematic literature review of mass appraisal models and methods from 2000 to 2018. The review focuses on the application trend and classification of mass appraisal and highlights a 3I-trend, namely AI-Based model, GIS-Based model and MIX-Based model. The characteristics of different mass appraisal models are analyzed and compared. Finally, the future trend of mass appraisal based on model perspective is defined as “mass appraisal 2.0”: mass appraisal is the appraisal procedure of model establishment, analysis and test of group of properties as of a given date, combined with artificial intelligence, geo-information systems, and mixed methods, to better model the real estate value of non-spatial and spatial data.

Suggested Citation

  • Daikun Wang & Victor Jing Li, 2019. "Mass Appraisal Models of Real Estate in the 21st Century: A Systematic Literature Review," Sustainability, MDPI, vol. 11(24), pages 1-14, December.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:24:p:7006-:d:295539
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    1. Glennon, Dennis & Kiefer, Hua & Mayock, Tom, 2018. "Measurement error in residential property valuation: An application of forecast combination," Journal of Housing Economics, Elsevier, vol. 41(C), pages 1-29.
    2. Chung Chun Lin & Satish B. Mohan, 2011. "Effectiveness comparison of the residential property mass appraisal methodologies in the USA," International Journal of Housing Markets and Analysis, Emerald Group Publishing Limited, vol. 4(3), pages 224-243, August.
    3. 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.
    4. Abdul-Rasheed Amidu & David Boyd, 2018. "Expert problem solving practice in commercial property valuation: an exploratory study," Journal of Property Investment & Finance, Emerald Group Publishing Limited, vol. 36(4), pages 366-382, July.
    5. Reyes-Bueno, Fabián & García-Samaniego, Juan Manuel & Sánchez-Rodríguez, Aminael, 2018. "Large-scale simultaneous market segment definition and mass appraisal using decision tree learning for fiscal purposes," Land Use Policy, Elsevier, vol. 79(C), pages 116-122.
    6. Sam K. Hui & Alvin Cheung & Jimmy Pang, 2010. "A Hierarchical Bayesian Approach for Residential Property Valuation:Application to Hong Kong Housing Market," International Real Estate Review, Global Social Science Institute, vol. 13(1), pages 1-29.
    7. Rotimi Boluwatife Abidoye & Albert P. C. Chan, 2017. "Modelling property values in Nigeria using artificial neural network," Journal of Property Research, Taylor & Francis Journals, vol. 34(1), pages 36-53, January.
    8. Jozef Zurada & Alan S. Levitan & Jian Guan, 2011. "A Comparison of Regression and Artificial Intelligence Methods in a Mass Appraisal Context," Journal of Real Estate Research, American Real Estate Society, vol. 33(3), pages 349-388.
    9. John Kilpatrick, 2011. "Expert systems and mass appraisal," Journal of Property Investment & Finance, Emerald Group Publishing Limited, vol. 29(4/5), pages 529-550, July.
    10. Narula, Subhash C. & Wellington, John F. & Lewis, Stephen A., 2012. "Valuating residential real estate using parametric programming," European Journal of Operational Research, Elsevier, vol. 217(1), pages 120-128.
    11. Vincenzo Del Giudice & Benedetto Manganelli & Pierfrancesco De Paola, 2017. "Hedonic Analysis of Housing Sales Prices with Semiparametric Methods," International Journal of Agricultural and Environmental Information Systems (IJAEIS), IGI Global, vol. 8(2), pages 65-77, April.
    12. David Lorenz & Thomas Lützkendorf, 2011. "Sustainability and property valuation," Journal of Property Investment & Finance, Emerald Group Publishing Limited, vol. 29(6), pages 644-676, September.
    13. Steven Bourassa & Eva Cantoni & Martin Hoesli, 2007. "Spatial Dependence, Housing Submarkets, and House Price Prediction," The Journal of Real Estate Finance and Economics, Springer, vol. 35(2), pages 143-160, August.
    14. David Tretton, 2007. "Where is the world of property valuation for taxation purposes going?," Journal of Property Investment & Finance, Emerald Group Publishing Limited, vol. 25(5), pages 482-514, August.
    15. Kerry D. Vandell, 2007. "Expanding the academic discipline of real estate valuation," Journal of Property Investment & Finance, Emerald Group Publishing Limited, vol. 25(5), pages 427-443, August.
    16. Iman Naderi & Ahmad Sharbatoghlie & Ahmadreza Vafaeimehr, 2012. "Housing valuation model: an investigation of residential properties in Tehran," International Journal of Housing Markets and Analysis, Emerald Group Publishing Limited, vol. 5(1), pages 20-40, March.
    17. Zhangcheng Chen & Yueming Hu & Chen Jason Zhang & Yilun Liu, 2017. "An Optimal Rubrics-Based Approach to Real Estate Appraisal," Sustainability, MDPI, vol. 9(6), pages 1-19, May.
    18. W.J. McCluskey & M. McCord & P.T. Davis & M. Haran & D. McIlhatton, 2013. "Prediction accuracy in mass appraisal: a comparison of modern approaches," Journal of Property Research, Taylor & Francis Journals, vol. 30(4), pages 239-265, December.
    19. Nancy Lozano-Gracia & Luc Anselin, 2012. "Is the price right?: Assessing estimates of cadastral values for Bogotá, Colombia," Regional Science Policy & Practice, Wiley Blackwell, vol. 4(4), pages 495-508, November.
    20. Uberti, Marlene Salete & Antunes, Mauro Antonio Homem & Debiasi, Paula & Tassinari, Wagner, 2018. "Mass appraisal of farmland using classical econometrics and spatial modeling," Land Use Policy, Elsevier, vol. 72(C), pages 161-170.
    21. Steffen Metzner & Andreas Kindt, 2017. "Determination of the parameters of automated valuation models for the hedonic property valuation of residential properties," International Journal of Housing Markets and Analysis, Emerald Group Publishing Limited, vol. 11(1), pages 73-100, December.
    22. Anselin, Luc, 2002. "Under the hood : Issues in the specification and interpretation of spatial regression models," Agricultural Economics, Blackwell, vol. 27(3), pages 247-267, November.
    23. Monica Palma & Claudia Cappello & Sandra De Iaco & Daniela Pellegrino, 2019. "The residential real estate market in Italy: a spatio-temporal analysis," Quality & Quantity: International Journal of Methodology, Springer, vol. 53(5), pages 2451-2472, September.
    24. Geltner, David & Goetzmann, William, 2000. "Two Decades of Commercial Property Returns: A Repeated-Measures Regression-Based Version of the NCREIF Index," The Journal of Real Estate Finance and Economics, Springer, vol. 21(1), pages 5-21, July.
    25. K.C. Lam & C.Y. Yu & C.K. Lam, 2009. "Support vector machine and entropy based decision support system for property valuation," Journal of Property Research, Taylor & Francis Journals, vol. 26(3), pages 213-233, August.
    26. Richard Buttimer & Steven H. Ott, 2007. "Commercial Real Estate Valuation, Development and Occupancy Under Leasing Uncertainty," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 35(1), pages 21-56, March.
    27. Kettani, Ossama & Oral, Muhittin, 2015. "Designing and implementing a real estate appraisal system: The case of Québec Province, Canada," Socio-Economic Planning Sciences, Elsevier, vol. 49(C), pages 1-9.
    28. Francesco Tajani & Pierluigi Morano & Klimis Ntalianis, 2018. "Automated valuation models for real estate portfolios," Journal of Property Investment & Finance, Emerald Group Publishing Limited, vol. 36(4), pages 324-347, July.
    29. William J. McCluskey & Richard A. Borst, 2011. "Detecting and validating residential housing submarkets," International Journal of Housing Markets and Analysis, Emerald Group Publishing Limited, vol. 4(3), pages 290-318, August.
    30. Salvatore Giuffrida & Filippo Gagliano & Francesco Nocera & Maria Rosa Trovato, 2018. "Landscape Assessment and Economic Accounting in Wind Farm Programming: Two Cases in Sicily," Land, MDPI, vol. 7(4), pages 1-20, October.
    31. Demetriou, Demetris, 2018. "Automating the land valuation process carried out in land consolidation schemes," Land Use Policy, Elsevier, vol. 75(C), pages 21-32.
    32. Shi-Ming Yu & Sun-Sheng Han & Chee-Hian Chai, 2007. "Modeling the Value of View in High-Rise Apartments: A 3D GIS Approach," Environment and Planning B, , vol. 34(1), pages 139-153, February.
    33. 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.
    34. Marc K. Francke & Gerjan A. Vos, 2004. "The Hierarchical Trend Model for Property Valuation and Local Price Indices," The Journal of Real Estate Finance and Economics, Springer, vol. 28(2_3), pages 179-208, March.
    35. Antipov, Evgeny & Pokryshevskaya, Elena, 2010. "Mass appraisal of residential apartments: An application of Random forest for valuation and a CART-based approach for model diagnostics," MPRA Paper 27645, University Library of Munich, Germany.
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    8. Renigier-Biłozor, Małgorzata & Źróbek, Sabina & Walacik, Marek & Borst, Richard & Grover, Richard & d’Amato, Maurizio, 2022. "International acceptance of automated modern tools use must-have for sustainable real estate market development," Land Use Policy, Elsevier, vol. 113(C).
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