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Combined asymmetric spatial weights matrix with application to housing prices

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  • Haiyong Zhang
  • Xinyu Wang

Abstract

In this study, a combined asymmetric spatial weights matrix is proposed for capturing the unequal spatial dependence of housing prices, where the advantage of this matrix was demonstrated by a non-nested hypothesis test. To explore the heterogeneous spatial impacts of urban essential characteristics on housing prices over the eastern, central, and western regions of China, after the Lagrange multiplier and likelihood ratio tests, the spatial Durbin model using the proposed weights matrix was applied to each region. The estimation results showed that the direct impacts of college and new employment were significantly negative in the eastern region, but not significant in the central and western regions. By contrast, the direct impacts of hospitals and scenic spots were significantly positive in eastern China, but not significant in central and western China. In addition, the indirect impacts of the four variables were not significant in the three regions. These results suggest that in eastern China, the government may increase the requirements for using medical resources and close tourist attractions in a single city to cool down the skyrocketing housing prices in this area.

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  • Haiyong Zhang & Xinyu Wang, 2017. "Combined asymmetric spatial weights matrix with application to housing prices," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(13), pages 2337-2353, October.
    • Handle: RePEc:taf:japsta:v:44:y:2017:i:13:p:2337-2353
    DOI: 10.1080/02664763.2016.1254163
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    Cited by:

    1. Haiyong Zhang & Xinyu Wang, 2018. "The impact of structural adjustment on housing prices in China," Asian-Pacific Economic Literature, The Crawford School, The Australian National University, vol. 32(1), pages 108-119, May.

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