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Using Latent Root Regression to Identify Nonpredictive Collinearity in Statistical Appraisal Models

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  • Alan K. Reichert
  • James S. Moore

Abstract

The objective of this study is to examine the potential benefits of using latent root regression techniques to improve the stability of appraisal coefficients (hedonic prices) over time. Another related objective is to more clearly identify the nature and implications of collinearity present in most appraisal models. The results indicate that the majority of the collinearity present in the data is of a predictive nature, hence latent root techniques will likely show little or no improvement over OLS models.

Suggested Citation

  • Alan K. Reichert & James S. Moore, 1986. "Using Latent Root Regression to Identify Nonpredictive Collinearity in Statistical Appraisal Models," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 14(1), pages 136-152, March.
    • Handle: RePEc:bla:reesec:v:14:y:1986:i:1:p:136-152
    DOI: 10.1111/1540-6229.00373
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    References listed on IDEAS

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    1. Rosen, Sherwin, 1974. "Hedonic Prices and Implicit Markets: Product Differentiation in Pure Competition," Journal of Political Economy, University of Chicago Press, vol. 82(1), pages 34-55, Jan.-Feb..
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    Cited by:

    1. Brent W. Ambrose, 1990. "An Analysis of the Factors Affecting Light Industrial Property Valuation," Journal of Real Estate Research, American Real Estate Society, vol. 5(3), pages 355-370.
    2. Otis W. Gilley & R. Kelley Pace, 1990. "A Hybrid Cost and Market-Based Estimator for Appraisal," Journal of Real Estate Research, American Real Estate Society, vol. 5(1), pages 75-88.

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