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Appraisal Using Generalized Additive Models

Many of the results from real estate empirical studies depend upon using a correct functional form for their validity. Unfortunately, common parametric statistical tools cannot easily control for the possibility of misspecification. Recently, semiparametric estimators such as generalized additive models (GAMs) have arisen which can automatically control for additive (in price) or multiplicative (in ln(price)) nonlinear relations among the independent and dependent variables. As the paper shows, GAMs can empirically outperform naive parametric and polynomial models in ex-sample predictive behavior. Moreover, GAMs have well-developed statistical properties and can suggest useful transformations in parametric settings.

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Article provided by American Real Estate Society in its journal Journal of Real Estate Research.

Volume (Year): 15 (1998)
Issue (Month): 1 ()
Pages: 77-100

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Handle: RePEc:jre:issued:v:15:n:1:1998:p:77-100
Contact details of provider: Postal: American Real Estate Society Clemson University School of Business & Behavioral Science Department of Finance 401 Sirrine Hall Clemson, SC 29634-1323
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Order Information: Postal: Diane Quarles American Real Estate Society Manager of Member Services Clemson University Box 341323 Clemson, SC 29634-1323
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  1. Anglin, Paul M & Gencay, Ramazan, 1996. "Semiparametric Estimation of a Hedonic Price Function," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 11(6), pages 633-48, Nov.-Dec..
  2. Coulson, N. Edward, 1989. "The empirical content of the linearity-as-repackaging hypothesis," Journal of Urban Economics, Elsevier, vol. 25(3), pages 295-309, May.
  3. Pace, R Kelley, 1993. "Nonparametric Methods with Applications to Hedonic Models," The Journal of Real Estate Finance and Economics, Springer, vol. 7(3), pages 185-204, November.
  4. Colwell, Peter F, 1991. "Functional Obsolescence and an Extension of Hedonic Theory," The Journal of Real Estate Finance and Economics, Springer, vol. 4(1), pages 49-58, March.
  5. Mark A. Sunderman & John W. Birch & Roger E. Cannaday & Thomas W. Hamilton, 1990. "Testing for Vertical Inequity in Property Tax Systems," Journal of Real Estate Research, American Real Estate Society, vol. 5(3), pages 319-334.
  6. Richard Meese & Nancy Wallace, 1991. "Nonparametric Estimation of Dynamic Hedonic Price Models and the Construction of Residential Housing Price Indices," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 19(3), pages 308-332.
  7. Haerdle,Wolfgang & Stoker,Thomas, 1987. "Investigations smooth multiple regression by the method of average derivatives," Discussion Paper Serie A 107, University of Bonn, Germany.
  8. Powell, James L & Stock, James H & Stoker, Thomas M, 1989. "Semiparametric Estimation of Index Coefficients," Econometrica, Econometric Society, vol. 57(6), pages 1403-30, November.
  9. A. Quang Do & G. Grudnitski, 1993. "A Neural Network Analysis of the Effect of Age on Housing Values," Journal of Real Estate Research, American Real Estate Society, vol. 8(2), pages 253-264.
  10. Hans R. Isakson, 1986. "The Nearest Neighbors Appraisal Technique: An Alternative to the Adjustment Grid Methods," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 14(2), pages 274-286.
  11. 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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