IDEAS home Printed from https://ideas.repec.org/a/eee/lauspo/v108y2021ics0264837721002623.html
   My bibliography  Save this article

Feature selection applications and model validation for mass real estate valuation systems

Author

Listed:
  • Yalpir, Sukran
  • Sisman, Suleyman
  • Akar, Ali Utku
  • Unel, Fatma Bunyan

Abstract

Real estate valuation, which has great importance in the country's economy, is one of the issues that cannot be resolved yet. The first of the most important problems in valuation is that the feature that affects the value is not clear, and the second is that the search for methods continues because the classical valuation methods are insufficient. Therefore, mass real estate valuation systems have been revealed. In current laws, the features for valuation are not standard and many different are used in each application, even if the real estate type is the same. Also, since the market conditions in the valuation of real estate are formed according to the supply-demand relationship, the subjective approaches cause the value to affect. In the mass valuation system that needs to be established, it is essential to determine the features that affect the value according to the real estate type and the characteristic of the region to be modeled. In this study, to determine the features needed to be addressed while the mass real estate valuation, a survey application was carried out located in the Central Anatolia region of Turkey Ankara, Konya, and Kayseri province. The survey application was conducted with both experts and citizens. Using survey questions, feature selection was made with Frequency Analysis (FRA), Principal Component Analysis (PCA), Factor Analysis (FA), and Analytical Hierarchy Process (AHP) approach. A total of 21 scenarios were created with participant groups from four different methods and indexing. According to the scenarios obtained from the methods applied as a result of the survey, the Multiple Regression (linear) Analysis method (MRA) was used to examine the verification of the features under market conditions. Three study regions were determined in Konya, and 21 scenario features created were implemented in study regions by the MRA method. The results of the study were examined by applying performance analysis.

Suggested Citation

  • Yalpir, Sukran & Sisman, Suleyman & Akar, Ali Utku & Unel, Fatma Bunyan, 2021. "Feature selection applications and model validation for mass real estate valuation systems," Land Use Policy, Elsevier, vol. 108(C).
    • Handle: RePEc:eee:lauspo:v:108:y:2021:i:c:s0264837721002623
    DOI: 10.1016/j.landusepol.2021.105539
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0264837721002623
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.landusepol.2021.105539?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Siqi Zheng & Jing Cao & Matthew Kahn & Cong Sun, 2014. "Real Estate Valuation and Cross-Boundary Air Pollution Externalities: Evidence from Chinese Cities," The Journal of Real Estate Finance and Economics, Springer, vol. 48(3), pages 398-414, April.
    2. Lucija Muehlenbachs & Elisheba Spiller & Christopher Timmins, 2015. "The Housing Market Impacts of Shale Gas Development," American Economic Review, American Economic Association, vol. 105(12), pages 3633-3659, December.
    3. Klaiber, H. Allen & Gopalakrishnan, Sathya, 2012. "The Impact of Shale Exploration on Housing Values in Pennsylvania," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 124368, Agricultural and Applied Economics Association.
    4. Renigier-Biłozor, Malgorzata & Janowski, Artur & d’Amato, Maurizio, 2019. "Automated Valuation Model based on fuzzy and rough set theory for real estate market with insufficient source data," Land Use Policy, Elsevier, vol. 87(C).
    5. Michael Doumpos & Dimitrios Papastamos & Dimitrios Andritsos & Constantin Zopounidis, 2020. "Developing automated valuation models for estimating property values: a comparison of global and locally weighted approaches," Post-Print hal-02880099, HAL.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Mehmet Özgür Çelik & Lütfiye Kuşak & Murat Yakar, 2024. "Assessment of Groundwater Potential Zones Utilizing Geographic Information System-Based Analytical Hierarchy Process, Vlse Kriterijumska Optimizacija Kompromisno Resenje, and Technique for Order Prefe," Sustainability, MDPI, vol. 16(5), pages 1-27, March.
    2. Sisman, S. & Aydinoglu, A.C., 2022. "Improving performance of mass real estate valuation through application of the dataset optimization and Spatially Constrained Multivariate Clustering Analysis," Land Use Policy, Elsevier, vol. 119(C).
    3. Unel, Fatma Bunyan & Yalpir, Sukran, 2023. "Sustainable tax system design for use of mass real estate appraisal in land management," Land Use Policy, Elsevier, vol. 131(C).

    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. Mei, Yingdan & Gao, Li & Zhang, Wendong & Yang, Feng-An, 2021. "Do homeowners benefit when coal-fired power plants switch to natural gas? Evidence from Beijing, China," Journal of Environmental Economics and Management, Elsevier, vol. 110(C).
    2. Sisman, S. & Aydinoglu, A.C., 2022. "Improving performance of mass real estate valuation through application of the dataset optimization and Spatially Constrained Multivariate Clustering Analysis," Land Use Policy, Elsevier, vol. 119(C).
    3. Brent W. Ambrose & Lily Shen, 2023. "Past Experiences and Investment Decisions: Evidence from Real Estate Markets," The Journal of Real Estate Finance and Economics, Springer, vol. 66(2), pages 300-326, February.
    4. Guignet, Dennis & Jenkins, Robin R. & Belke, James & Mason, Henry, 2023. "The property value impacts of industrial chemical accidents," Journal of Environmental Economics and Management, Elsevier, vol. 120(C).
    5. Hashida, Yukiko & Dundas, Steven J., 2023. "The effects of a voluntary property buyout and acquisition program on coastal housing markets: Evidence from New York," Journal of Environmental Economics and Management, Elsevier, vol. 121(C).
    6. Hoy, Kyle A. & Wrenn, Douglas H., 2018. "Unconventional energy, taxation, and interstate welfare: An analysis of Pennsylvania's severance tax policy," Energy Economics, Elsevier, vol. 73(C), pages 53-65.
    7. David A Keiser & Joseph S Shapiro, 2019. "Consequences of the Clean Water Act and the Demand for Water Quality," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 134(1), pages 349-396.
    8. Cronshaw, Ian & Grafton, R. Quentin, 2016. "Economic benefits, external costs and the regulation of unconventional gas in the United States," Energy Policy, Elsevier, vol. 98(C), pages 180-186.
    9. Steve Gibbons & Stephan Heblich & Esther Lho & Christopher Timmins, 2016. "Fear of Fracking? The Impact of the Shale Gas Exploration on House Prices in Britain," SERC Discussion Papers 0207, Centre for Economic Performance, LSE.
    10. Xu, Shang & Allen Klaiber, H., 2019. "The impact of new natural gas pipelines on emissions and fuel consumption in China," Resource and Energy Economics, Elsevier, vol. 55(C), pages 49-62.
    11. Guoying Deng & Manuel A. Hernandez & Shu Xu, 2020. "When Power Plants Leave Town: Environmental Quality and the Housing Market in China," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 77(4), pages 751-780, December.
    12. Funke, Michael & Leiva-Leon, Danilo & Tsang, Andrew, 2019. "Mapping China’s time-varying house price landscape," Regional Science and Urban Economics, Elsevier, vol. 78(C).
    13. Bishop, Kelly C. & Kuminoff, Nicolai V. & Mathes, Sophie M. & Murphy, Alvin D., 2024. "The marginal cost of mortality risk reduction: Evidence from housing markets," Journal of Urban Economics, Elsevier, vol. 139(C).
    14. Iris Claus & Les Oxley & Siqi Zheng & Cong Sun & Ye Qi & Matthew E. Kahn, 2014. "The Evolving Geography Of China'S Industrial Production: Implications For Pollution Dynamics And Urban Quality Of Life," Journal of Economic Surveys, Wiley Blackwell, vol. 28(4), pages 709-724, September.
    15. Dan S. Rickman, 2014. "Assessing Regional Quality of Life: A Call for Action in Regional Science," The Review of Regional Studies, Southern Regional Science Association, vol. 44(1), pages 1-12, Spring.
    16. Heyes, Anthony & Zhu, Mingying, 2019. "Air pollution as a cause of sleeplessness: Social media evidence from a panel of Chinese cities," Journal of Environmental Economics and Management, Elsevier, vol. 98(C).
    17. Rivera, Nathaly M. & Loveridge, Scott, 2022. "Coal-to-gas fuel switching and its effects on housing prices," Energy Economics, Elsevier, vol. 106(C).
    18. Pedro Gete & Michael Reher, 2018. "Mortgage Supply and Housing Rents," The Review of Financial Studies, Society for Financial Studies, vol. 31(12), pages 4884-4911.
    19. Lade, Gabriel E. & Rudik, Ivan, 2020. "Costs of inefficient regulation: Evidence from the Bakken," Journal of Environmental Economics and Management, Elsevier, vol. 102(C).
    20. Elizabeth U. Cascio & Ayushi Narayan, 2022. "Who Needs a Fracking Education? The Educational Response to Low-Skill-Biased Technological Change," ILR Review, Cornell University, ILR School, vol. 75(1), pages 56-89, January.

    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:eee:lauspo:v:108:y:2021:i:c:s0264837721002623. 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: Joice Jiang (email available below). General contact details of provider: https://www.journals.elsevier.com/land-use-policy .

    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.