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

Author

Listed:
  • Stanley McGreal

    (University of Ulster, UK)

  • Paloma Taltavull de La Paz

    (University of Alicante, Spain)

  • Valerie Kupke

    (University of South Australia, Australia)

  • Peter Rossini

    (University of South Australia, Australia)

  • Paul Kershaw

    (University of South Australia, Australia)

Abstract

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.

Suggested Citation

  • Stanley McGreal & Paloma Taltavull de La Paz & Valerie Kupke & Peter Rossini & Paul Kershaw, 2016. "Measuring the influence of space and time effects on time on the market," Urban Studies, Urban Studies Journal Limited, vol. 53(13), pages 2867-2884, October.
  • Handle: RePEc:sae:urbstu:v:53:y:2016:i:13:p:2867-2884
    DOI: 10.1177/0042098015596923
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    References listed on IDEAS

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    Cited by:

    1. Liang, Cong & Hui, Eddie C.M. & Yip, Tsz Leung, 2018. "Time on market (TOM): The impact of new residential stamp duty," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 1117-1130.
    2. Liang, Cong & Hui, Eddie C.M. & Yip, Tsz Leung & Huang, Yaoxuan, 2020. "Private land use for public housing projects: The Influence of a Government Announcement on Housing Markets in Hong Kong," Land Use Policy, Elsevier, vol. 99(C).
    3. Neil T Coffee & Tony Lockwood & Peter Rossini & Theo Niyonsenga & Stanley McGreal, 2020. "Composition and context drivers of residential property location value as a socioeconomic status measure," Environment and Planning B, , vol. 47(5), pages 790-807, June.
    4. Lockwood, Tony & Coffee, Neil T & Rossini, Peter & Niyonsenga, Theo & McGreal, Stanley, 2018. "Does where you live influence your socio-economic status?," Land Use Policy, Elsevier, vol. 72(C), pages 152-160.

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