IDEAS home Printed from https://ideas.repec.org/a/spr/snbeco/v2y2022i11d10.1007_s43546-022-00358-4.html
   My bibliography  Save this article

Predicting residential property value: a comparison of multiple regression techniques

Author

Listed:
  • Lee Whieldon

    (University of Maryland, Baltimore County)

  • Huthaifa I. Ashqar

    (Precision Systems, Inc.
    Arab American University)

Abstract

This study aims to predict the prices of residential properties in Catonsville, MD based on publicly available tax assessment data maintained by Maryland government institutions. Recent legislation in Maryland has made it a requirement for local governments to provide up-to-date, easily accessible data to its constituents. This study used three regression techniques: linear, ridge, and lasso regression. Extracting over 11,000 property records from Maryland’s Open Data Portal (ODP), we applied regression techniques to predict the price. We used various independent features to predict the price of residential properties including prior year housing sales price, size of house, house age, street address type (single family or townhouse), if the house has a basement, dwelling type, number of stories, and dwelling grade (scale from 1 to 6). Outperforming lasso and ridge regression, linear regression can enhance the predictability of housing prices and significantly contribute to the correct evaluation of real estate price using only two years of historical data and without additional socioeconomic variables. We also found that among others, prior year housing sales price (positive), size of house (negative), and house age (positive) are the most significant factors in predicting housing sales price in Catonsville, MD.

Suggested Citation

  • Lee Whieldon & Huthaifa I. Ashqar, 2022. "Predicting residential property value: a comparison of multiple regression techniques," SN Business & Economics, Springer, vol. 2(11), pages 1-16, November.
    • Handle: RePEc:spr:snbeco:v:2:y:2022:i:11:d:10.1007_s43546-022-00358-4
    DOI: 10.1007/s43546-022-00358-4
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s43546-022-00358-4
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s43546-022-00358-4?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. Hao Wu & Hongzan Jiao & Yang Yu & Zhigang Li & Zhenghong Peng & Lingbo Liu & Zheng Zeng, 2018. "Influence Factors and Regression Model of Urban Housing Prices Based on Internet Open Access Data," Sustainability, MDPI, vol. 10(5), pages 1-17, May.
    2. Crone, Theodore M. & Voith, Richard P., 1992. "Estimating house price appreciation: A comparison of methods," Journal of Housing Economics, Elsevier, vol. 2(4), pages 324-338, December.
    3. Jim Clayton, 1996. "Rational Expectations, Market Fundamentals and Housing Price Volatility," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 24(4), pages 441-470, December.
    4. Susane Leguizamon, 2010. "The Influence of Reference Group House Size on House Price," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 38(3), pages 507-527, September.
    5. Bradford Case & John Clapp & Robin Dubin & Mauricio Rodriguez, 2004. "Modeling Spatial and Temporal House Price Patterns: A Comparison of Four Models," The Journal of Real Estate Finance and Economics, Springer, vol. 29(2), pages 167-191, September.
    Full references (including those not matched with items on IDEAS)

    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. Lee Whieldon & Huthaifa Ashqar, 2020. "Predicting Residential Property Value in Catonsville, Maryland: A Comparison of Multiple Regression Techniques," Papers 2101.01531, arXiv.org.
    2. Paloma Taltavull de La Paz, 2021. "Predicting housing prices. A long term housing price path for Spanish regions," LARES lares-2021-4dra, Latin American Real Estate Society (LARES).
    3. Colin Jones & Chris Leishman, 2006. "Spatial Dynamics of the Housing Market: An Interurban Perspective," Urban Studies, Urban Studies Journal Limited, vol. 43(7), pages 1041-1059, June.
    4. Jamie Spinney & Pavlos Kanaroglou & Darren Scott, 2011. "Exploring Spatial Dynamics with Land Price Indexes," Urban Studies, Urban Studies Journal Limited, vol. 48(4), pages 719-735, March.
    5. Stefan Sebastian Fahrländer, 2006. "Semiparametric Construction of Spatial Generalized Hedonic Models for Private Properties," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 142(IV), pages 501-528, December.
    6. Juergen Deppner & Marcelo Cajias, 2024. "Accounting for Spatial Autocorrelation in Algorithm-Driven Hedonic Models: A Spatial Cross-Validation Approach," The Journal of Real Estate Finance and Economics, Springer, vol. 68(2), pages 235-273, February.
    7. Crowe, Christopher & Dell’Ariccia, Giovanni & Igan, Deniz & Rabanal, Pau, 2013. "How to deal with real estate booms: Lessons from country experiences," Journal of Financial Stability, Elsevier, vol. 9(3), pages 300-319.
    8. Liang Peng, 2012. "Repeat Sales Regression on Heterogeneous Properties," The Journal of Real Estate Finance and Economics, Springer, vol. 45(3), pages 804-827, October.
    9. Ayuso, Juan & Restoy, Fernando, 2007. "House prices and rents in Spain: Does the discount factor matter?," Journal of Housing Economics, Elsevier, vol. 16(3-4), pages 291-308, November.
    10. Chica-Olmo, Jorge & Cano-Guervos, Rafael, 2020. "Does my house have a premium or discount in relation to my neighbors? A regression-kriging approach," Socio-Economic Planning Sciences, Elsevier, vol. 72(C).
    11. Tsang, Chun-Kei & Wong, Wing-Keung & Horowitz, Ira, 2016. "A stochastic-dominance approach to determining the optimal home-size purchase: The case of Hong Kong," MPRA Paper 69175, University Library of Munich, Germany.
    12. Zahirovich-Herbert, Velma & Gibler, Karen M., 2014. "The effect of new residential construction on housing prices," Journal of Housing Economics, Elsevier, vol. 26(C), pages 1-18.
    13. Mr. Luis M. Cubeddu & Mr. Camilo E Tovar Mora & Ms. Evridiki Tsounta, 2012. "Latin America: Vulnerabilities Under Construction?," IMF Working Papers 2012/193, International Monetary Fund.
    14. Kristoffer B. Birkeland & Allan D. D'Silva & Roland Füss & Are Oust, 2021. "The Predictability of House Prices: "Human Against Machine"," International Real Estate Review, Global Social Science Institute, vol. 24(2), pages 139-183.
    15. Marko Kryvobokov, 2011. "Defining apartment neighbourhoods with Thiessen polygons and fuzzy equality clustering," ERES eres2011_142, European Real Estate Society (ERES).
    16. Denis Conniffe & David Duffy, 1999. "Irish House Price Indices — Methodological Issues," The Economic and Social Review, Economic and Social Studies, vol. 30(4), pages 403-423.
    17. Foryś Iwona, 2010. "Apartment Price Indices on the Example of Cooperative Apartments Sale Transactions," Folia Oeconomica Stetinensia, Sciendo, vol. 9(1), pages 72-82, January.
    18. Jorge Chica-Olmo, 2007. "Prediction of Housing Location Price by a Multivariate Spatial Method: Cokriging," Journal of Real Estate Research, American Real Estate Society, vol. 29(1), pages 95-114.
    19. McCluskey, Jill J. & Rausser, Gordon C., 2003. "Hazardous waste sites and housing appreciation rates," Journal of Environmental Economics and Management, Elsevier, vol. 45(2), pages 166-176, March.
    20. David Duffy, 2001. "The Use of Location Variables in a Mix-Adjusted Index for Dublin House Prices," Papers WP138, Economic and Social Research Institute (ESRI).

    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:spr:snbeco:v:2:y:2022:i:11:d:10.1007_s43546-022-00358-4. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.