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Estimation, Interpretation, and Hypothesis Testing for Nonparametric Hedonic House Price Functions

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  • Daniel P. McMillen
  • Christopher Redfearn

Abstract

Despite well-documented shortcomings, hedonic and repeat sales estimators remain the most widely used methods for constructing quality controlled house price indexes and for assessing housing attribute capitalization into dwelling prices. Nonparametric estimators overcome many of the problems associated with these approaches by controlling for misspecified spatial effects while using highly flexible forms. Despite these advantages, nonparametric procedures are still not used extensively for data analysis due to perceived difficulties associated with estimation and hypothesis testing. We demonstrate that nonparametric estimation is both feasible for large data sets with many explanatory variables and offers significant advantages in terms of the information content of the estimates. These features are demonstrated in an application of valuing capitalization of access to a rapid transit line into surrounding dwelling prices.

Suggested Citation

  • Daniel P. McMillen & Christopher Redfearn, 2007. "Estimation, Interpretation, and Hypothesis Testing for Nonparametric Hedonic House Price Functions," Working Paper 8550, USC Lusk Center for Real Estate.
    • Handle: RePEc:luk:wpaper:8550
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    References listed on IDEAS

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    Cited by:

    1. Wu, Wenjie, 2012. "Spatial variations in amenity values: new evidence from Beijing, China," LSE Research Online Documents on Economics 58536, London School of Economics and Political Science, LSE Library.
    2. repec:ehu:biltok:5463 is not listed on IDEAS
    3. Potrawa, Tomasz & Tetereva, Anastasija, 2022. "How much is the view from the window worth? Machine learning-driven hedonic pricing model of the real estate market," Journal of Business Research, Elsevier, vol. 144(C), pages 50-65.
    4. Redfearn, Christian L., 2009. "How informative are average effects? Hedonic regression and amenity capitalization in complex urban housing markets," Regional Science and Urban Economics, Elsevier, vol. 39(3), pages 297-306, May.

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