Measuring the influence of space and time effects on time on the market.

This paper is concerned with spatial effects of time on the market for residential property and time varying relationships using a dataset of properties from the Adelaide metropolitan area, Australia, during the period 2002–2011. The analysis firstly considers the spatial dependence in time on the m...

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Publicado en:Urban Studies (Sage Publications, Ltd.) Vol. 53; no. 13; pp. 2867 - 2885
Autores principales: McGreal, Stanley, Taltavull de La Paz, Paloma, Kupke, Valerie, Rossini, Peter, Kershaw, Paul
Formato: Artículo
Publicado: Sage Publications, Ltd. Oct2016
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Oct2016
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        atl: Measuring the influence of space and time effects on time on the market.
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        au:
          McGreal, Stanley
          Taltavull de La Paz, Paloma
          Kupke, Valerie
          Rossini, Peter
          Kershaw, Paul
        affil:
          University of Ulster, UK
          University of Alicante, Spain
          University of South Australia, Australia
      su:
        Metropolitan areas
        Business cycles
        Spacetime
        Home prices
        Spatial analysis (Statistics)
        Liquidity (Economics)
      sug:
        subj:
          Metropolitan areas
          Business cycles
          Central credit unions
          Financial Transactions Processing, Reserve, and Clearinghouse Activities
          Spacetime
          Home prices
          Spatial analysis (Statistics)
          Liquidity (Economics)
      keyword:
        Adelaide metropolitan area
        house prices
        space-time models
        spatial analysis
        time on the market
        Adelaide metropolitan area
        house prices
        space-time models
        spatial analysis
        time on the market
      ab: This paper is concerned with spatial effects of time on the market for residential property and time varying relationships using a dataset of properties from the Adelaide metropolitan area, Australia, during the period 2002–2011. The analysis firstly considers the spatial dependence in time on the market and secondly extends the analysis to a space-time model using 2SLS regression. The findings demonstrate the complexity in spatial analysis with results indicating a random distribution of time on the market in 86% of observations a pattern that is consistent over time. Spatial autocorrelation is shown to increase time on the market in the subject property while spatial error decreases time on the market in the subject property suggesting a high level of market transparency and improved liquidity. The compensating or nullifying effects of both types of spatial association is shown to contribute to the random distribution observed in time on the market. A strong explanatory capacity of the business cycle suggests that economic drivers are leading time on the market rather than prices.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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