IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v217y2012i1p120-128.html
   My bibliography  Save this article

Valuating residential real estate using parametric programming

Author

Listed:
  • Narula, Subhash C.
  • Wellington, John F.
  • Lewis, Stephen A.

Abstract

When the estimation of the single equation multiple linear regression model is looked upon as an optimization problem, we show how the principles and methods of optimization can assist the analyst in finding an attractive prediction model. We illustrate this with the estimation of a linear prediction model for valuating residential property using regression quantiles. We make use of the linear parametric programming formulation to obtain the family of regression quantile models associated with a data set. We use the principle of dominance to reduce the number of models for consideration in the search for the most preferred property valuation model (s). We also provide useful displays that assist the analyst and the decision maker in selecting the final model (s). The approach is an interface between data analysis and operations research.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:ejores:v:217:y:2012:i:1:p:120-128
    DOI: 10.1016/j.ejor.2011.08.014
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377221711007557
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ejor.2011.08.014?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. Marcos Lins & Luiz Novaes & Luiz Legey, 2005. "Real Estate Appraisal: A Double Perspective Data Envelopment Analysis Approach," Annals of Operations Research, Springer, vol. 138(1), pages 79-96, September.
    2. 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.
    3. Narula, Subhash C. & Wellington, John F., 2007. "Multiple criteria linear regression," European Journal of Operational Research, Elsevier, vol. 181(2), pages 767-772, September.
    4. Koenker,Roger, 2005. "Quantile Regression," Cambridge Books, Cambridge University Press, number 9780521845731, September.
    5. Ihlanfeldt, Keith R. & Martinez-Vazquez, Jorge, 1986. "Alternative value estimates of owner-occupied housing: Evidence on sample selection bias and systematic errors," Journal of Urban Economics, Elsevier, vol. 20(3), pages 356-369, November.
    6. Timothy P. Cronan & Donald R. Epley & Larry G. Perry, 1986. "The Use of Rank Transformation and Multiple Regression Analysis in Estimating Residential Property Values With A Small Sample," Journal of Real Estate Research, American Real Estate Society, vol. 1(1), pages 19-31.
    7. 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.
    8. Ball, J'Noel & Srinivasan, Venkat C, 1994. "Using the Analytic Hierarchy Process in House Selection," The Journal of Real Estate Finance and Economics, Springer, vol. 9(1), pages 69-85, July.
    9. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    10. Aragones-Beltran, P. & Aznar, J. & Ferris-Onate, J. & Garcia-Melon, M., 2008. "Valuation of urban industrial land: An analytic network process approach," European Journal of Operational Research, Elsevier, vol. 185(1), pages 322-339, February.
    11. Koenker, Roger & Bassett, Gilbert, Jr, 1982. "Robust Tests for Heteroscedasticity Based on Regression Quantiles," Econometrica, Econometric Society, vol. 50(1), pages 43-61, January.
    12. Roger Koenker & Kevin F. Hallock, 2001. "Quantile Regression," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 143-156, Fall.
    13. Aznar, Jeronimo & Guijarro, Francisco, 2007. "Estimating regression parameters with imprecise input data in an appraisal context," European Journal of Operational Research, Elsevier, vol. 176(3), pages 1896-1907, February.
    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. 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).
    2. Dieudonné Tchuente & Serge Nyawa, 2022. "Real estate price estimation in French cities using geocoding and machine learning," Annals of Operations Research, Springer, vol. 308(1), pages 571-608, January.
    3. Michalis Doumpos & Dimitrios Papastamos & Dimitrios Andritsos & Constantin Zopounidis, 2021. "Developing automated valuation models for estimating property values: a comparison of global and locally weighted approaches," Annals of Operations Research, Springer, vol. 306(1), pages 415-433, November.
    4. Xiangqian Li & Keke Li & Yaxin Tian & Siqi Shen & Yue Yu & Liwei Jin & Pengyu Meng & Jingjing Cao & Xiaoxiao Zhang, 2024. "Decision Support for Carbon Emission Reduction Strategies in China’s Cement Industry: Prediction and Identification of Influencing Factors," Sustainability, MDPI, vol. 16(13), pages 1-17, June.
    5. 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.
    6. William Suley Menges & Kevin Getii Moranga, 2020. "Indirect investment and financial performance of the real estate sector in Nairobi County Kenya," Bussecon Review of Finance & Banking (2687-2501), Bussecon International, vol. 2(1), pages 25-34, January.
    7. Lessmann, Stefan & Voß, Stefan, 2017. "Car resale price forecasting: The impact of regression method, private information, and heterogeneity on forecast accuracy," International Journal of Forecasting, Elsevier, vol. 33(4), pages 864-877.
    8. William Suley Menges & Kevin Getii Moranga, 2019. "Indirect investment and financial performance of the real estate sector in Nairobi county Kenya," International Journal of Business Ecosystem & Strategy (2687-2293), Bussecon International Academy, vol. 1(4), pages 09-18, October.
    9. Shawn L. Robey & Mark A McKnight & Misty R. Price & Rachel N. Coleman, 2019. "Considerations for a Regression-Based Real Estate Valuation and Appraisal Model: A Pilot Study," Accounting and Finance Research, Sciedu Press, vol. 8(2), pages 1-99, May.

    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. Huber, Martin & Melly, Blaise, 2011. "Quantile Regression in the Presence of Sample Selection," Economics Working Paper Series 1109, University of St. Gallen, School of Economics and Political Science.
    2. Yang, Lu & Tian, Shuairu & Yang, Wei & Xu, Mingli & Hamori, Shigeyuki, 2018. "Dependence structures between Chinese stock markets and the international financial market: Evidence from a wavelet-based quantile regression approach," The North American Journal of Economics and Finance, Elsevier, vol. 45(C), pages 116-137.
    3. Komunjer, Ivana, 2013. "Quantile Prediction," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 961-994, Elsevier.
    4. Muller, Christophe, 2018. "Heterogeneity and nonconstant effect in two-stage quantile regression," Econometrics and Statistics, Elsevier, vol. 8(C), pages 3-12.
    5. Jean-Marc Fournier & Isabell Koske, 2012. "The determinants of earnings inequality: evidence from quantile regressions," OECD Journal: Economic Studies, OECD Publishing, vol. 2012(1), pages 7-36.
    6. Duschl, Matthias & Schimke, Antje & Brenner, Thomas & Luxen, Dennis, 2011. "Firm growth and the spatial impact of geolocated external factors: Empirical evidence for German manufacturing firms," Working Paper Series in Economics 36, Karlsruhe Institute of Technology (KIT), Department of Economics and Management.
    7. Agbeyegbe, Terence D., 2015. "An inverted U-shaped crude oil price return-implied volatility relationship," Review of Financial Economics, Elsevier, vol. 27(C), pages 28-45.
    8. Ordu, Beyza Mina & Oran, Adil & Soytas, Ugur, 2018. "Is food financialized? Yes, but only when liquidity is abundant," Journal of Banking & Finance, Elsevier, vol. 95(C), pages 82-96.
    9. Gaglianone, Wagner Piazza & Lima, Luiz Renato & Linton, Oliver & Smith, Daniel R., 2011. "Evaluating Value-at-Risk Models via Quantile Regression," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(1), pages 150-160.
    10. Chowdhury, Biplob & Jeyasreedharan, Nagaratnam & Dungey, Mardi, 2018. "Quantile relationships between standard, diffusion and jump betas across Japanese banks," Journal of Asian Economics, Elsevier, vol. 59(C), pages 29-47.
    11. Christophe Muller, 2019. "Linear Quantile Regression and Endogeneity Correction," Biostatistics and Biometrics Open Access Journal, Juniper Publishers Inc., vol. 9(5), pages 123-128, August.
    12. Tanya O’Garra & Susana Mourato, 2007. "Public Preferences for Hydrogen Buses: Comparing Interval Data, OLS and Quantile Regression Approaches," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 36(4), pages 389-411, April.
    13. Frondel, Manuel & Ritter, Nolan & Vance, Colin, 2012. "Heterogeneity in the rebound effect: Further evidence for Germany," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 34(2), pages 461-467.
    14. Jamal Bouoiyour & Refk Selmi, 2017. "The Bitcoin price formation: Beyond the fundamental sources," Working Papers hal-01548710, HAL.
    15. Mohamed S. Ahmed & John A. Doukas, 2021. "Revisiting disposition effect and momentum: a quantile regression perspective," Review of Quantitative Finance and Accounting, Springer, vol. 56(3), pages 1087-1128, April.
    16. Wiji Arulampalam & Alison Booth & Mark Bryan, 2010. "Are there asymmetries in the effects of training on the conditional male wage distribution?," Journal of Population Economics, Springer;European Society for Population Economics, vol. 23(1), pages 251-272, January.
    17. Marrocu, Emanuela & Paci, Raffaele & Zara, Andrea, 2015. "Micro-economic determinants of tourist expenditure: A quantile regression approach," Tourism Management, Elsevier, vol. 50(C), pages 13-30.
    18. Javier Alejo, 2013. "Relación de Kuznets en América Latina. Explorando más allá de la media condicional," Económica, Departamento de Economía, Facultad de Ciencias Económicas, Universidad Nacional de La Plata, vol. 59, pages 3-55, January-D.
    19. Joachim Wagner, 2014. "Exports, foreign direct investments and productivity: are services firms different?," The Service Industries Journal, Taylor & Francis Journals, vol. 34(1), pages 24-37, January.
    20. Jiang, Rong & Qian, Weimin & Zhou, Zhangong, 2012. "Variable selection and coefficient estimation via composite quantile regression with randomly censored data," Statistics & Probability Letters, Elsevier, vol. 82(2), pages 308-317.

    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:ejores:v:217:y:2012:i:1:p:120-128. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eor .

    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.