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Local Polynomial Regressions versus OLS for Generating Location Value Estimates

Author

Listed:
  • Jeffrey P. Cohen

    (University of Connecticut)

  • Cletus C. Coughlin

    (Federal Reserve Bank of St. Louis)

  • John M. Clapp

    (University of Connecticut
    Reading University)

Abstract

We estimate location values for single family houses using a standard house price and characteristics dataset and local polynomial regressions (LPR), a procedure that allows for complex interactions between the values of structural characteristics and the value of land. We also compare LPR to additive OLS models in the Denver metropolitan area with out-of-sample methods. We determine that the LPR model is more efficient than OLS at predicting location values in counties with greater densities of sales. Also, LPR outperforms OLS in 2010 for all counties in our dataset. Our findings suggest that LPR is a preferable approach in areas with greater concentrations of sales and in periods of recovery following a financial crisis.

Suggested Citation

  • Jeffrey P. Cohen & Cletus C. Coughlin & John M. Clapp, 2017. "Local Polynomial Regressions versus OLS for Generating Location Value Estimates," The Journal of Real Estate Finance and Economics, Springer, vol. 54(3), pages 365-385, April.
    • Handle: RePEc:kap:jrefec:v:54:y:2017:i:3:d:10.1007_s11146-016-9570-3
    DOI: 10.1007/s11146-016-9570-3
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    References listed on IDEAS

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    Cited by:

    1. Enwei Zhu & Jing Wu & Hongyu Liu & Xindian Li, 2022. "Within‐City Spatial Distribution, Heterogeneity and Diffusion of House Price: Evidence from a Spatiotemporal Index for Beijing," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 50(3), pages 621-655, September.
    2. Jeffrey P. Cohen & Cletus C. Coughlin & Jeffrey Zabel, 2020. "Time-Geographically Weighted Regressions and Residential Property Value Assessment," The Journal of Real Estate Finance and Economics, Springer, vol. 60(1), pages 134-154, February.
    3. Antonio Nesticò & Marianna La Marca, 2020. "Urban Real Estate Values and Ecosystem Disservices: An Estimate Model Based on Regression Analysis," Sustainability, MDPI, vol. 12(16), pages 1-15, August.
    4. John M. Clapp & Jeffrey P. Cohen & Thies Lindenthal, 2023. "Are Estimates of Rapid Growth in Urban Land Values an Artifact of the Land Residual Model?," The Journal of Real Estate Finance and Economics, Springer, vol. 66(2), pages 373-421, February.
    5. Roland Füss & Jan A. Koller & Alois Weigand, 2021. "Determining Land Values from Residential Rents," Land, MDPI, vol. 10(4), pages 1-29, March.

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    More about this item

    Keywords

    Land values; Location values; Semi-parametric estimation; Local polynomial regressions;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • R51 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Regional Government Analysis - - - Finance in Urban and Rural Economies
    • R53 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Regional Government Analysis - - - Public Facility Location Analysis; Public Investment and Capital Stock
    • H41 - Public Economics - - Publicly Provided Goods - - - Public Goods
    • H54 - Public Economics - - National Government Expenditures and Related Policies - - - Infrastructures

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