Comparing hedonic models for estimating and forecasting house prices

In published work on hedonic house price estimation it is not uncommon to examine some of the conditions required for the estimators to have desirable properties such as minimum variance and unbiasedness, in particular spatial autocorrelation. However, other conditions that can give rise to similar difficulties with the estimates are often ignored. If these technical conditions are not met, it is sometimes because the model is misspecified in some way. This paper argues that a wider range of diagnostic statistics should be used in the specification search for a good model, in particular, but not exclusively, those concerned with predictive stability. The paper illustrates this approach by examining both in‐sample and out‐of‐sample diagnostic tests of various specifications of a hedonic house price model using data taken from the sale of over 1,600 properties in the Midlands of the UK in 1999/2000. The models investigated include various specifications of the dependent and independent variables, including models that are non‐linear in the parameters. The paper concludes that such statistics can often help in model selection and should be more widely employed.

[1]  David W. Rasmussen,et al.  Measuring the impact of crime on house prices , 2001 .

[2]  R Ward,et al.  AIRCRAFT NOISE AND RESIDENTIAL PROPERTY VALUES ADJACENT TO MANCHESTER INTERNATIONAL AIRPORT , 1990 .

[3]  L. Drake.  Modelling UK house prices using cointegration: an application of the Johansen technique , 1993 .

[4]  Craig Watkins.  Property valuation and the structure of urban housing markets , 1999 .

[5]  Aysegul Can.  The Measurement of Neighborhood Dynamics in Urban House Prices , 1990 .

[6]  David M. Brasington.  Which Measures of School Quality Does the Housing Market Value , 2000 .

[7]  D. Rubinfeld,et al.  Econometric models and economic forecasts , 2002 .

[8]  Martin Hoesli,et al.  A hedonic investigation of the rental value of apartments in central Bordeaux , 1997 .

[9]  William J. McCluskey,et al.  The application of surface generated interpolation models for the prediction of residential property values , 2000 .

[10]  Yong Tu,et al.  Economic perspectives on the structure of local housing systems , 1996 .

[11]  C. Jarque,et al.  An efficient large-sample test for normality of observations and regression residuals , 1981 .

[12]  J. B. Ramsey,et al.  Tests for Specification Errors in Classical Linear Least‐Squares Regression Analysis , 1969 .

[13]  M. Fletcher,et al.  The modelling of housing submarkets , 2000 .

[14]  Clive W. J. Granger,et al.  Forecasting in Business and Economics. , 1981 .

[15]  William M. Bowen,et al.  Theoretical and Empirical Considerations Regarding Space in Hedonic Housing Price Model Applications , 2001 .

[16]  Robert A. Simons,et al.  The Effects of An Oil Pipeline Rupture on Single Family House Prices , 2001 .

[17]  M. Thériault,et al.  Environment and value Does drinking water quality affect house prices , 1999 .

[18]  Jim Berry,et al.  Hedonic modelling, housing submarkets and residential valuation , 1996 .

[19]  G. Chow.  Tests of equality between sets of coefficients in two linear regressions (econometrics voi 28 , 1960 .

[20]  John Mangan,et al.  Heteroscedasticity in hedonic house price models , 2000 .

[21]  Brian A. Mikelbank,et al.  Theoretical and Empirical Considerations Regarding Space in Hedonic Housing Price Models , 2001 .

[22]  Roger Koenker,et al.  A note on studentizing a test for heteroscedasticity , 1981 .

[23]  Marius Thériault,et al.  Sorting out access and neighbourhood factors in hedonic price modelling , 1999 .