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

Livingston, M. , Pannullo, F. , Bowman, A. W. , Scott, E. M. and Bailey, N. (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 (Statistics in Society), 184(2), pp. 663-682. (doi: 10.1111/rssa.12643)

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.

• Item Type: Articles
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Bailey, Professor Nick and Scott, Professor Marian and Pannullo, Miss Francesca and Livingston, Dr Mark and Bowman, Prof Adrian
• Authors: Livingston, M., Pannullo, F., Bowman, A. W., Scott, E. M., and Bailey, N.
• College/School: College of Science and Engineering > School of Mathematics and Statistics; College of Social Sciences > School of Social and Political Sciences > Urban Studies
• Journal Name: Journal of the Royal Statistical Society: Series A (Statistics in Society)
• Publisher: Wiley
• ISSN: 0964-1998
• ISSN (Online): 1467-985X
• Published Online: 09 January 2021
• Copyright Holders: Copyright © 2021 The Authors
• First Published: First published in Journal of the Royal Statistical Society: Series A (Statistics in Society) 184(2): 663-682
• Publisher Policy: Reproduced under a Creative Commons License

Project Code	Award No	Project Name	Principal Investigator	Funder's Name	Funder Ref	Lead Dept
190698		Urban Big Data Research Centre	Nick Bailey	Economic and Social Research Council (ESRC)	ES/L011921/1	S&PS - Urban Big Data
304042		UBDC Centre Transition	Nick Bailey	Economic and Social Research Council (ESRC)	ES/S007105/1	S&PS - Administration