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Spatial and Temporal Dependence in House Price Prediction

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Abstract

This paper incorporates spatial and temporal dependence among housing transactions in predicting future house prices. We employ the spatiotemporal autoregressive model and structure the spatial and temporal weighting matrices as in Pace et al. (1998). We control for the time variation of both the attribute prices and the spatial and temporal dependence parameters through performing the analysis on an annual basis. Spatial heterogeneity is accounted for using experience-based definition of submarkets by real estate professionals. Using a comprehensive housing transaction data set from the Dutch Randstad region, we show that integrating the spatial and temporal dependence within the hedonic modeling improves the prediction power as compared to traditional hedonic model that neglects these effects.

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Notes

  1. See Dubin (1998) for the details of these two modeling approaches.

  2. As noted in Pace et al. (1998), the interaction terms essentially account for the order of filtering both the dependent and the independent variables, especially when we do not have prior knowledge on which, space or time, to filter first.

  3. Pace et al. (1998) discuss the choice of the equal weight attached to each of the prior transaction to the current transaction which is based on an acceptable performance from preliminary fitting.

  4. Results for other years are available upon request.

  5. See, for example, Plackett (1950).

  6. For the sake of space, results are not included in the paper and are available upon request.

  7. Broker region 34 includes Amsterdam. Broker region 42 includes Utrecht. Broker 46 includes The Hague. Broker region 49 includes Rotterdam.

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Acknowledgements

The author is grateful to Peter Englund, Marc Francke and Martin Hoesli for their constructive and valuable comments and suggestions. He would also like to thank the Dutch Association of Real Estate Brokers and Real Estate Experts (NVM) for providing the data for this research. In addition, he thanks the editor and the anonymous referee of this journal for their comments. Any remaining errors are the author’s responsibility.

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  1. School of Finance, Renmin University of China, No. 59, Zhongguancun Main Street, Haidian District, Beijing, 100872, China

    Xiaolong Liu

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Liu, X. Spatial and Temporal Dependence in House Price Prediction. J Real Estate Finan Econ 47, 341–369 (2013). https://doi.org/10.1007/s11146-011-9359-3

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