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Exploiting new forms of data to study the private rented sector: Strengths and limitations of a database of rental listings

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Listed:
  • Mark Livingston
  • Francesca Pannullo
  • Adrian W. Bowman
  • E. Marian Scott
  • Nick Bailey

Abstract

Reviews of official statistics for UK housing have noted that developments have not kept pace with real‐world change, particularly the rapid growth of private renting. This paper examines the potential value of big data in this context. We report on the construction of a dataset from the on‐line adverts of one national lettings agency, describing the content of the dataset and efforts to validate it against external sources. The paper specifically examines what these data might add to our understanding of changing volumes and rents in the private rented sector. Fluctuations in market share across advertising platforms make assessment of volume problematic, while rental prices appear more robust through comparison with other reference information. Focussing on one urban area, we illustrate how the dataset can shed new light on local changes. Lastly, we discuss the issues involved in making more routine use of this kind of data.

Suggested Citation

  • Mark Livingston & Francesca Pannullo & Adrian W. Bowman & E. Marian Scott & Nick Bailey, 2021. "Exploiting new forms of data to study the private rented sector: Strengths and limitations of a database of rental listings," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(2), pages 663-682, April.
    • Handle: RePEc:bla:jorssa:v:184:y:2021:i:2:p:663-682
    DOI: 10.1111/rssa.12643
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    References listed on IDEAS

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    1. Harvey J. Miller, 2010. "The Data Avalanche Is Here. Shouldn’T We Be Digging?," Journal of Regional Science, Wiley Blackwell, vol. 50(1), pages 181-201, February.
    2. Peter A. Kemp, 2015. "Private Renting After the Global Financial Crisis," Housing Studies, Taylor & Francis Journals, vol. 30(4), pages 601-620, July.
    3. Adrian W. Bowman & Marco Giannitrapani & E. Marian Scott, 2009. "Spatiotemporal smoothing and sulphur dioxide trends over Europe," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 58(5), pages 737-752, December.
    4. Adrian W. Bowman, 2019. "Graphics for uncertainty," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 182(2), pages 403-418, February.
    5. Halford, Susan & Savage, Mike, 2017. "Speaking sociologically with big data: symphonic social science and the future for big data research," LSE Research Online Documents on Economics 87236, London School of Economics and Political Science, LSE Library.
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