Analyzing the Temporal Stability of Appraisal Model Coefficients: An Application of Ridge Regression Techniques | Zendy

Moore James S. | Zendy; Reicheri Alan K. | Zendy; Cho ChienChing | Zendy

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Analyzing the Temporal Stability of Appraisal Model Coefficients: An Application of Ridge Regression Techniques

Author(s) -

Moore James S.,

Reicheri Alan K.,

Cho ChienChing

Publication year - 1984

Publication title -

real estate economics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 1.064

H-Index - 61

eISSN - 1540-6229

pISSN - 1080-8620

DOI - 10.1111/1540-6229.00310

Subject(s) - multicollinearity , regression , statistics , regression analysis , regression diagnostic , econometrics , mathematics , collinearity , linear regression , ridge , segmented regression , local regression , polynomial regression , ordinary least squares , stability (learning theory) , cross sectional regression , computer science , geology , machine learning , paleontology

The use of multiple regression analysis as a tool of real estate valuation has received considerable attention in recent years. The primary objectives of this study are to investigate the multicollinearity among the property characteristics (regressor variables) and examine the stability of the estimated regression coefficients over time. Ridge regression techniques are used to partially adjust for the presence of collinearity. The results indicate that the ridge regression model provides a consistent set of properly signed, statistically significant regression coefficients throughout the sample period. Furthermore, ridge regression techniques are shown to have certain advantages over those of ordinary least squares for establishing logical and consistent values for specific property characteristics.

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