Each week, we select a recently published Open Access article to feature. This week’s article comes from Journal of the Royal Statistical Society Series A (Statistics in Society) and considers the potential of big data in studying the private rented sector.

The article’s abstract is given below, with the full article available to read here.

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. J R Stat Soc Series A. https://doi.org/10.1111/rssa.12643

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.