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Prediction in the lognormal regression model with spatial error dependence

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  • Kato, Takafumi

Abstract

In the context of the lognormal regression model with spatial error dependence, the present study examines correction of a bias in prediction. If interest lies in the predicted mean value of the dependent variable, antilogarithmic transformation of the predicted mean value of the regressand produces a bias. In order to correct such a transformation bias, we derive several alternative predictors by extending some of the predictors suggested for the lognormal regression model with spherical disturbances. Behaviors of our predictors are described in a theoretical manner, and their performances are assessed in an experimental manner. Extension of an asymptotically unbiased predictor is shown to be useful.

Suggested Citation

  • Kato, Takafumi, 2012. "Prediction in the lognormal regression model with spatial error dependence," Journal of Housing Economics, Elsevier, vol. 21(1), pages 66-76.
    • Handle: RePEc:eee:jhouse:v:21:y:2012:i:1:p:66-76
    DOI: 10.1016/j.jhe.2012.01.003
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    1. James P. LeSage & R. Kelley Pace, 2004. "Models for Spatially Dependent Missing Data," The Journal of Real Estate Finance and Economics, Springer, vol. 29(2), pages 233-254, September.
    2. Takafumi Kato, 2008. "Response To Comment On “A Further Exploration Into The Robustness Of Spatial Autocorrelation Specifications”," Journal of Regional Science, Wiley Blackwell, vol. 48(3), pages 651-653, August.
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    6. Steven Bourassa & Eva Cantoni & Martin Hoesli, 2007. "Spatial Dependence, Housing Submarkets, and House Price Prediction," The Journal of Real Estate Finance and Economics, Springer, vol. 35(2), pages 143-160, August.
    7. Halvorsen, Robert & Palmquist, Raymond, 1980. "The Interpretation of Dummy Variables in Semilogarithmic Equations," American Economic Review, American Economic Association, vol. 70(3), pages 474-475, June.
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    More about this item

    Keywords

    Lognormal regression model; Spatial error dependence; Transformation bias;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • R21 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Housing Demand
    • R31 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Housing Supply and Markets

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