Property appraisal via lens of property registration abundance – real estate market asymmetry assessment
Abstract
Information on transaction prices and the ones characterizing the property as the subject of the valuation are essential for a proper valuation process. The accuracy and completeness of the collected set of information directly affects the quality of the valuation process. When market participants operate on the basis of unequal sets of information, information asymmetry is revealed. This research investigates the effects of information asymmetry on property market from the perspective of property registration abundance and mass appraisal systems. It explores how disparities in information abundance and quality within property registration and appraisal processes can affect market fairness and transparency. Employing a mixed-methods approach, it analyses property transaction data and tries to investigate effects of information asymmetry. The findings indicate that enhanced transparency and data quality can significantly reduce valuation discrepancies and lead to a more equitable real estate market. The study concludes with recommendations aimed at justifying information asymmetry’s negative effects, supporting for policies that promote information uniformity to improve the fairness and efficiency of property registration and mass appraisal practices.
Keyword : information asymmetry, property valuation, random forest, neural networks, multiple linear regression
How to Cite
Walacik, M. (2024). Property appraisal via lens of property registration abundance – real estate market asymmetry assessment. International Journal of Strategic Property Management, 28(6), 393–410. https://doi.org/10.3846/ijspm.2024.22686
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
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d’Amato, M., & Kauko, T. (2017). Appraisal methods and the non-agency mortgage crisis. In M. d’Amato & T. Kauko (Eds.), Advances in automated valuation modeling: AVM after the non-agency mortgage crisis (pp. 23–32). Springer International Publishing. https://doi.org/10.1007/978-3-319-49746-4_2
Danastri Yuwono, A., Khairunnisa, A., Ikasanti, M., Adilah, N., & Widiyani, W. (2023). Pendekatan highest and best use dalam pelestarian bangunan bersejarah. Arsitektura: Jurnal Ilmiah Arsitektur dan Lingkungan Binaan, 21(2), 247–260. https://doi.org/10.20961/arst.v21i2.77861
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Fletcher, R. (2000). Practical methods of optimization. John Wiley & Sons, Ltd. https://doi.org/10.1002/9781118723203
Garmaise, M. J., & Moskowitz, T. J. (2004). Confronting information asymmetries: Evidence from real estate markets. The Review of Financial Studies, 17(2), 405–437. https://doi.org/10.1093/RFS/HHG037
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Gdakowicz, A., Putek-Szeląg, E., & Kuźmiński, W. (2019). Information asymmetry and mass appraisal. Metody Ilościowe w Badaniach Ekonomicznych, 20(3), 149–166. https://doi.org/10.22630/MIBE.2019.20.3.15
Ho, T. K. (1995). Random decision forests. In Proceedings of the International Conference on Document Analysis and Recognition (Vol. 1, pp. 278–282). IEEE. https://doi.org/10.1109/ICDAR.1995.598994
Ho, T. K. (1998). The random subspace method for constructing decision forests. IEEE Transactions on Pattern Analysis and Machine Intelligence, 20(8), 832–844. https://doi.org/10.1109/34.709601
Hong, J., & Kim, W. (2022). Combination of machine learning-based automatic valuation models for residential properties in South Korea. International Journal of Strategic Property Management, 26(5), 362–384. https://doi.org/10.3846/IJSPM.2022.17909
Huber, R., D’Onofrio, C., Devaraju, A., Klump, J., Loescher, H. W., Kindermann, S., Guru, S., Grant, M., Morris, B., Wyborn, L., Evans, B., Goldfarb, D., Genazzio, M. A., Ren, X., Magagna, B., Thiemann, H., & Stocker, M. (2021). Integrating data and analysis technologies within leading environmental research infrastructures: Challenges and approaches. Ecological Informatics, 61, Article 101245. https://doi.org/10.1016/J.ECOINF.2021.101245
Ionascu, E., Mironiuc, M., & Anghel, I. (2019). Transparency of real estate markets: Conceptual and empirical evidence. Audit Financiar, 17(154), 306–326. https://doi.org/10.20869/AUDITF/2019/154/013
Johnson, K. H., Springer, T. H., & Brockman, C. M. (2005). Price effects of non-traditionally broker-marketed properties. The Journal of Real Estate Finance and Economics, 31, 331–343. https://doi.org/10.1007/s11146-005-2793-3
Jung, J., Kim, J., & Jin, C. (2022). Does machine learning prediction dampen the information asymmetry for non-local investors? International Journal of Strategic Property Management, 26(5), 345–361. https://doi.org/10.3846/IJSPM.2022.17590
Keskin, B., & Watkins, C. (2017). Defining spatial housing submarkets: Exploring the case for expert delineated boundaries. Urban Studies, 54(6), 1446–1462. https://doi.org/10.1177/0042098015620351
Klein, T. J., Lambertz, C., & Stahl, K. O. (2016). Market transparency, adverse selection, and moral hazard. Journal of Political Economy, 124(6), 1677–1713. https://doi.org/10.1086/688875
Kurlat, P., & Stroebel, J. (2014). Testing for information asymmetries in real estate markets (Working Paper No. 19875). National Bureau of Economic Research. https://doi.org/10.3386/w19875
Levitt, S. D., & Syverson, C. (2008). Market distortions when agents are better informed: The value of information in real estate transactions. The Review of Economics and Statistics, 90(4), 599–611. https://doi.org/10.1162/rest.90.4.599
Li, L., & Chau, K. W. (2024). Information asymmetry with heterogeneous buyers and sellers in the housing market. Journal of Real Estate Finance and Economics, 68(1), 138–159. https://doi.org/10.1007/s11146-023-09939-y
Ling, D. C., Naranjo, A., & Petrova, M. T. (2018). Search costs, behavioral biases, and information intermediary effects. The Journal of Real Estate Finance and Economics, 57, 114–151. https://doi.org/10.1007/s11146-016-9582-z
Meszek, W., & Dziadosz, A. (2011). Wpływ nieefektywności rynku nieruchomości na dokładność opisu wartości nieruchomości za pomocą liniowych modeli regresji wielorakiej. Budownictwo i Inżynieria Środowiska, 2(4), 589–594.
Morley, S. K., Brito, T. V., & Welling, D. T. (2018). Measures of model performance based on the log accuracy ratio. Space Weather, 16(1), 69–88. https://doi.org/10.1002/2017SW001669
Murphy, A. H. (1993). What is a good forecast? An essay on the nature of goodness in weather forecasting. Weather and Forecasting, 8(2), 281–293. 2.0.CO;2> https://doi.org/10.1175/1520-0434(1993)008<0281:WIAGFA>2.0.CO;2
Ogryzek, M. (2023). The sustainable development paradigm. Geomatics and Environmental Engineering, 17(1), 5–18. https://doi.org/10.7494/geom.2023.17.1.5
Ragil Budi Perkasa, A., Utomo, C., & Budi Santoso, E. (2023). A review of research methods on highest and best use for toll rest area. Materials Today: Proceedings, 85, 19–23. https://doi.org/10.1016/j.matpr.2023.05.247
Renigier-Bilozor, M., Janowski, A., & Walacik, M. (2019). Geoscience methods in real estate market analyses subjectivity decrease. Geosciences, 9(3), Article 130. https://doi.org/10.3390/geosciences9030130
Renigier-Biłozor, M., Janowski, A., Walacik, M., & Chmielewska, A. (2022). Modern challenges of property market analysis-homogeneous areas determination. Land Use Policy, 119, Article 106209. https://doi.org/10.1016/j.landusepol.2022.106209
Ribera, F., Nesticò, A., Cucco, P., & Maselli, G. (2020). A multicriteria approach to identify the highest and best use for historical buildings. Journal of Cultural Heritage, 41, 166–177. https://doi.org/10.1016/j.culher.2019.06.004
Ries, A., & Trout, J. (1994). The 22 immutable laws of marketing: Violate them at your own risk! https://archive.org/details/22immutablelawso00alri/page/n1/mode/2up
Royal Institution of Chartered Surveyors. (2022). Automated valuation models (AVMs): Implications for the profession and their clients. Royal Institution of Chartered Surveyors (RICS).
Rymarzak, M., Siemińska, E., & Sakierski, K. (2022). Reflecting sustainability in the analysis of highest and best use: Evidence from Polish municipalities. Real Estate Management and Valuation, 30(4), 103–115. https://doi.org/10.2478/remav-2022-0032
Sayce, S., & Connellan, O. (2002). From existing use to value in use: Time for a paradigm shift? Property Management, 20(4), 228–251. https://doi.org/10.1108/02637470210444268
Sayce, S., Smith, J., Cooper, R., & Venmore-Rowland, P. (2006). Real estate appraisal: From value to worth. Wiley-Blackwell.
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