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Research Article

Automated valuation models: improving model performance by choosing the optimal spatial training level

, ORCID Icon, , &
Pages 365-390 | Received 14 Oct 2022, Accepted 18 Apr 2023, Published online: 02 May 2023

References

  • Akiba, T., Sano, S., Yanase, T., Ohta, T., & Koyama, M. (2019). Optuna: A next-generation hyperparameter optimization framework. In Proceedings of the 25th ACM SIGKDD international conference on knowledge discovery & data mining (pp. 2623–2631).
  • Antipov, E. A., & Pokryshevskaya, E. B. (2012). Mass appraisal of residential apartments: An application of Random forest for valuation and a CART-based approach for model diagnostics. Expert Systems with Applications, 39(2), 1772–1778. https://doi.org/10.1016/j.eswa.2011.08.077
  • Baldominos, A., Blanco, I., Moreno, A., Iturrarte, R., Bernárdez, Ó., & Afonso, C. (2018). Identifying Real Estate Opportunities Using Machine Learning. Applied Sciences, 8(11), 2321. https://doi.org/10.3390/app8112321
  • Bankers Association, M. (2019). The State of Automated Valuation Models in the Age of Big Data. Washington DC.
  • Bourassa, S. C., Cantoni, E., & Hoesli, M. (2008). Predicting House Prices with Spatial Dependence: Impacts of Alternative Submarket Definitions. Social Science Research Network Electronic Journal. https://doi.org/10.2139/ssrn.1090147
  • Bunke, O., Droge, B., & Polzehl, J. (1999). Model Selection, Transformations and Variance Estimation in Nonlinear Regression. Statistics, 33(3), 197–240. https://doi.org/10.1080/02331889908802692
  • Cajias, M., Willwersch, J., & Lorenz, F. (2019). I know where you will invest in the next year – Forecasting real estate investments with machine learning methods. European Real Estate Society (ERES). ERES. https://ideas.repec.org/p/arz/wpaper/eres2019_171.html
  • Chau, K. W., & Chin, T. L. (2002). A Critical Reveiw of the Literature on the Hedonic Pricing Model and Its aplication to the Housing Market in Penang. In Proceedings of the The Seventh Asian Real Estate Society Conference.
  • Chun Lin, C., & Mohan, S. B. (2011). Effectiveness comparison of the residential property mass appraisal methodologies in the USA. International Journal of Housing Markets and Analysis, 4(3), 224–243. https://doi.org/10.1108/17538271111153013
  • Dąbrowski, J., & Adamczyk, T. (2010). Application of GAM additive non-linear models to estimate real estate market value. Geomatics and Environmental Engineering, 4(2), 55–62.
  • Fahrmeir, L., Kneib, T., Lang, S., & Marx, B. (2013). Regression: Models, Methods and Applications. Springer-Verlag.
  • Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep Learning. MIT Press.
  • Handy, S. L., & Clifton, K. J. (2001). Evaluating Neighborhood Accessibility: Possibilities and Practicalities. Journal of Transportation and Statistics, 4(2), 67–78.
  • Hastie, T., Friedman, J., & Tibshirani, R. (2001). The Elements of Statistical Learning. Springer New York. https://doi.org/10.1007/978-0-387-21606-5
  • Hastie, T., & Tibshirani, R. (1987). Generalized additive models: Some applications. Journal of the American Statistical Association, 82(398), 371–386.
  • Hong, J., Choi, H., & Kim, W. (2020). A House Price Valuation based on Random Forest Approach: The Mass Appraisal of Residential Property in South Korea. International Journal of Strategic Property Management, 24(3), 140–152. https://doi.org/10.3846/ijspm.2020.11544
  • Huang, Y., & Dall’erba, S. (2021). Does Proximity to School Still Matter Once Access to Your Preferred School Zone Has Already Been Secured? The Journal of Real Estate Finance and Economics, 62(4), 548–577. https://doi.org/10.1007/s11146-020-09761-w
  • Just, T., & Maennig, W. (Eds.). (2012). Understanding German Real Estate Markets. Springer. https://doi.org/10.1007/978-3-642-23611-2
  • Just, T., & Schaefer, P. (2017). Germany’s Regional Structure. Understanding German Real Estate Markets, 41–57. https://doi.org/10.1007/978-3-642-23611-2
  • Kok, N., Koponen, E. ‑., & Martínez-Barbosa, C. A. (2017). Big Data in Real Estate? From Manual Appraisal to Automated Valuation. The Journal of Portfolio Management, 43(6), 202–211. https://doi.org/10.3905/jpm.2017.43.6.202
  • Lancaster, K. J. (1966). A New Approach to Consumer Theory. The Journal of Political Economy, 74(2), 132–157. https://doi.org/10.1086/259131
  • Malpezzi, S. (2003). Hedonic Pricing Models: A Selective and Applied Review. Housing Economics and Public Policy, 67–89. Original work published 2003. https://doi.org/10.1002/9780470690680.ch5
  • Mayer, M., Bourassa, S. C., Hoesli, M., & Scognamiglio, D. (2019). Estimation and updating methods for hedonic valuation. Journal of European Real Estate Research, 12(1), 134–150. https://doi.org/10.1108/JERER-08-2018-0035
  • McCluskey, W., Davis, P., Haran, M. [., McCord, M. [., & McIlhatton, D. [. (2012). The potential of artificial neural networks in mass appraisal: The case revisited. Journal of Financial Management of Property and Construction, 17(3), 274–292. https://doi.org/10.1108/13664381211274371
  • McCluskey, W. J., McCord, M., Davis, P. T., Haran, M., & McIlhatton, D (2013). Prediction accuracy in mass appraisal: A comparison of modern approaches. Journal of Property Research, 30(4), 239–265. https://doi.org/10.1080/09599916.2013.781204
  • Metzner, S., & Kindt, A. (2018). Determination of the parameters of automated valuation models for the hedonic property valuation of residential properties. International Journal of Housing Markets and Analysis, 11(1), 73–100. https://doi.org/10.1108/IJHMA-02-2017-0018
  • Nghiep, N., & Al, C. (2001). Predicting Housing Value: A Comparison of Multiple Regression Analysis and Artificial Neural Networks. Journal of Real Estate Research, 22(3), 313–336. https://doi.org/10.1080/10835547.2001.12091068
  • Nobis, C., & Kuhnimhof, T. (2018). Mobilität in Deutschland − MiD: Ergebnisbericht, Bonn.
  • Osland, L. (2010). An Application of Spatial Econometrics in Relation to Hedonic House Price Modeling. Journal of Real Estate Research, 32(3), 289–320. https://doi.org/10.1080/10835547.2010.12091282
  • Pace, R. K. (1998). Appraisal Using Generalized Additive Models. Journal of Real Estate Research, 15(1), 77–99. https://doi.org/10.1080/10835547.1998.12090916
  • Pace, R. K., & Hayunga, D. (2020). Examining the Information Content of Residuals from Hedonic and Spatial Models Using Trees and Forests. The Journal of Real Estate Finance and Economics, 60(1–2), 170–180. https://doi.org/10.1007/s11146-019-09724-w
  • Pace, R. K., & LeSage, J. (2004). Spatial Statistics and Real Estate. The Journal of Real Estate Finance and Economics, 29(2), 147–148. https://doi.org/10.1023/b:real.0000035307.99686.fb
  • Páez, A., Long, F., & Farber, S. (2008). Moving Window Approaches for Hedonic Price Estimation: An Empirical Comparison of Modelling Techniques. Urban Studies, 45(8), 1565–1581. https://doi.org/10.1177/0042098008091491
  • Pham, D. T. (1970). Neural Networks in Engineering. WIT Transactions on Information and Communication Technologies, 6, 3–36. https://doi.org/10.2495/AI940011
  • Powe, N. A., Garrod, G. D., & Willis, K. G. (1995). Valuation of urban amenities using an hedonic price model. Journal of Property Research, 12(2), 137–147. https://doi.org/10.1080/09599919508724137
  • Rosen, S. (1974). Hedonic Prices and Implicit Markets: Product Differentiation in Pure Competition. The Journal of Political Economy, 82(1), 34–55. https://doi.org/10.1086/260169
  • Schulz, R., Wersing, M., & Werwatz, A. (2014). Automated valuation modelling: A specification exercise. Journal of Property Research, 31(2), 131–153. https://doi.org/10.1080/09599916.2013.846930
  • Sirmans, S., Macpherson, D., & Zietz, E. (2005). The Composition of Hedonic Pricing Models. Journal of Real Estate Literature, 13(1), 1–44. https://doi.org/10.1080/10835547.2005.12090154
  • Stang, M., Krämer, B., Nagl, C., & Schäfers, W. (2022). From human business to machine learning—Methods for automating real estate appraisals and their practical implications. Zeitschrift Für Immobilienökonomie, 1–28. https://doi.org/10.1365/s41056-022-00063-1
  • Tse, R. Y. C. (2002). Estimating Neighbourhood Effects in House Prices: Towards a New Hedonic Model Approach. Urban Studies, 39(7), 1165–1180. https://doi.org/10.1080/00420980220135545
  • Wood, S. N. (2017). Generalized Additive Models: An Introduction with R, Second Edition. CRC Press.
  • Yang, J., Bao, Y., Zhang, Y., Li, X., & Ge, Q. (2018). Impact of Accessibility on Housing Prices in Dalian City of China Based on a Geographically Weighted Regression Model. Chinese Geographical Science, 28(3), 505–515. https://doi.org/10.1007/s11769-018-0954-6
  • Yao, Y., Zhang, J., Hong, Y., Liang, H., & He, J. (2018). Mapping fine-scale urban housing prices by fusing remotely sensed imagery and social media data. Transactions in GIS, 22(2), 561–581. https://doi.org/10.1111/tgis.12330
  • Yilmazer, S., & Kocaman, S. (2020). A mass appraisal assessment study using machine learning based on multiple regression and random forest. Land Use Policy, 99, 104889. https://doi.org/10.1016/j.landusepol.2020.104889
  • Yoo, S., Im, J., & Wagner, J. E. (2012). Variable selection for hedonic model using machine learning approaches: A case study in Onondaga County, NY. Landscape and Urban Planning, 107(3), 293–306. https://doi.org/10.1016/j.landurbplan.2012.06.009
  • Zurada, J., Levitan, A., & Guan, J. (2011). A Comparison of Regression and Artificial Intelligence Methods in a Mass Appraisal Context. Journal of Real Estate Research, 33(3), 349–388. https://doi.org/10.1080/10835547.2011.12091311

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